\vspace{.1cm} Students directly advised or co-advised \underline{in underline}. \vspace{.4cm} \headedsection{{\bf Assistive Technology}}{}{ \begin{enumerate} \item Sonya S. Nikolova, {\bf Jordan Boyd-Graber}, and Christiane Fellbaum. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2011_book_chapter_evocation.pdf}{Collecting Semantic Similarity Ratings to Connect Concepts in Assistive Communication Tools}}. \emph{Modeling, Learning and Processing of Text Technological Data Structures}, 2011, 11 pages. \item Sonya S. Nikolova, {\bf Jordan Boyd-Graber}, Christiane Fellbaum, and Perry Cook. {\bf \href{http://umiacs.umd.edu/~jbg//docs/evocation-viva.pdf}{Better Vocabularies for Assistive Communication Aids: Connecting Terms using Semantic Networks and Untrained Annotators}}. \emph{ACM Conference on Computers and Accessibility}, 2009, 8 pages (31\% Acceptance Rate). \item Xiaojuan Ma, {\bf Jordan Boyd-Graber}, Sonya S. Nikolova, and Perry Cook. {\bf \href{http://umiacs.umd.edu/~jbg//docs/image_icon.pdf}{Speaking Through Pictures: Images vs. Icons}}. \emph{ACM Conference on Computers and Accessibility}, 2009, 8 pages (31\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, Sonya S. Nikolova, Karyn A. Moffatt, Kenrick C. Kin, Joshua Y. Lee, Lester W. Mackey, Marilyn M. Tremaine, and Maria M. Klawe. {\bf \href{http://umiacs.umd.edu/~jbg//docs/paper673-boyd-graber.pdf}{Participatory design with proxies: {D}eveloping a desktop-{PDA} system to support people with aphasia}}. \emph{Computer-Human Interaction}, 2006, 10 pages (23\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Bayesian Non-parametrics}}{}{ \begin{enumerate} \item Daniel Peterson, {\bf Jordan Boyd-Graber}, Martha Palmer, and Daisuke Kawahara. {\bf \href{https://aclanthology.org/S16-2012/}{Leveraging {V}erb{N}et to build Corpus-Specific Verb Clusters}}. \emph{Proceedings of the Fifth Joint Conference on Lexical and Computational Semantics}, 2016, 5 pages. \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Philip Resnik, Deborah Cai, Jennifer Midberry, and Yuanxin Wang. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_mlj_influencer.pdf}{Modeling Topic Control to Detect Influence in Conversations using Nonparametric Topic Models}}. \emph{Machine Learning}, 2014, 48 pages. \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, {\bf Jordan Boyd-Graber}, and Shay B. Cohen. {\bf Hybrid Online Inference with Adaptor Grammars}. \emph{NIPS Workshop on Advances in Variational Inference}, 2014. \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Philip Resnik, and Jonathan Chang. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_nips_l2h.pdf}{Learning a Concept Hierarchy from Multi-labeled Documents}}. \emph{Neural Information Processing Systems}, 2014, 9 pages (25\% Acceptance Rate). \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, {\bf Jordan Boyd-Graber}, and Shay B. Cohen. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_tacl_ag_vb_online.pdf}{Online Adaptor Grammars with Hybrid Inference}}. \emph{Transactions of the Association for Computational Linguistics}, 2014, 12 pages. \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_icml_infvoc.pdf}{Online Topic Models with Infinite Vocabulary}}. \emph{International Conference on Machine Learning}, 2013, 9 pages (20\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, and Stephen Altschul. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_dp_protein.pdf}{Dirichlet Mixtures, the Dirichlet Process, and the Structure of Protein Space}}. \emph{Journal of Computational Biology}, 2013, 48 pages. \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, Hal {Daum\'{e} III}, and Z. Irene Ying. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_coalescent.pdf}{Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent}}. \emph{Neural Information Processing Systems}, 2013, 9 pages (25\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_shlda.pdf}{Lexical and Hierarchical Topic Regression}}. \emph{Neural Information Processing Systems}, 2013, 10 pages (25\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_argviz.pdf}{Argviz: Interactive Visualization of Topic Dynamics in Multi-party Conversations}}. \emph{North American Association for Computational Linguistics}, 2013, 4 pages (50\% Acceptance Rate). \item Naho Orita, Rebecca McKeown, Naomi H. Feldman, Jeffrey Lidz, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_cogsci_pronoun.pdf}{Discovering Pronoun Categories using Discourse Information}}. \emph{Proceedings of the Cognitive Science Society}, 2013, 6 pages. \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/acl_2012_sits.pdf}{{SITS}: A Hierarchical Nonparametric Model using Speaker Identity for Topic Segmentation in Multiparty Conversations}}. \emph{Association for Computational Linguistics}, 2012, 10 pages (19\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, Sinead Williamson, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/mtibp_icml_2012.pdf}{Modeling Images using Transformed {I}ndian Buffet Processes}}. \emph{International Conference on Machine Learning}, 2012, 8 pages (27\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}} and {\bf Jordan Boyd-Graber}. {\bf Bayesian Hierarchical Clustering with Beta Coalescents}. \emph{Mid-Atlantic Student Colloquium on Speech, Language, and Learning}, 2012. \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}} and {\bf Jordan Boyd-Graber}. {\bf Online Topic Model with Infinite Vocabulary}. \emph{Mid-Atlantic Student Colloquium on Speech, Language, and Learning}, 2012. \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf ``I Want to Talk About, Again, My Record On Energy~\dots'': Modeling Topic Control in Conversations using Speaker-centric Nonparametric Topic Models}. \emph{Mid-Atlantic Student Colloquium on Speech, Language, and Learning}, 2012. \item \underline{Eric Hardisty}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/adapted_naive_bayes.pdf}{Modeling Perspective using Adaptor Grammars}}. \emph{Empirical Methods in Natural Language Processing}, 2010, 10 pages (25\% Acceptance Rate). \item {\bf Jordan Boyd-Graber} and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/nips2008.pdf}{Syntactic Topic Models}}. \emph{Neural Information Processing Systems}, 2008, 8 pages (25\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Computational Biology}}{}{ \begin{enumerate} \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, and Stephen Altschul. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_dp_protein.pdf}{Dirichlet Mixtures, the Dirichlet Process, and the Structure of Protein Space}}. \emph{Journal of Computational Biology}, 2013, 48 pages. \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, Hal {Daum\'{e} III}, and Z. Irene Ying. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_coalescent.pdf}{Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent}}. \emph{Neural Information Processing Systems}, 2013, 9 pages (25\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Data Mining}}{}{ \begin{enumerate} \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_emnlp_mtm.pdf}{A Multilingual Topic Model for Learning Weighted Topic Links Across Incomparable Corpora}}. \emph{Empirical Methods in Natural Language Processing}, 2019, 6 pages. \item Aaron Gerow, Yuening Hu, {\bf Jordan Boyd-Graber}, David M. Blei, and James A. Evans. {\bf Measuring Discursive Influence Across Scholarship}. \emph{Proceedings of the National Academies of Science}, 2018. \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_emnlp_tree_prior.pdf}{Adapting Topic Models using Lexical Associations with Tree Priors}}. \emph{Empirical Methods in Natural Language Processing}, 2017, 6 pages (18\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_acl_docblock.pdf}{A Discriminative Topic Model using Document Network Structure}}. \emph{Association for Computational Linguistics}, 2016, 10 pages (28\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf Birds of a Feather in the Same Nest: A Discriminative Topic Model using Block-based Priors}. \emph{Mid-Atlantic Student Colloquium on Speech, Language, and Learning}, 2016. \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Anupam Guha, Snigdha Chaturvedi, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_relationships.pdf}{Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships}}. \emph{North American Association for Computational Linguistics}, 2016, 11 pages (24\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_emnlp_hinge_link.pdf}{Birds of a Feather Linked Together: A Discriminative Topic Model using Link-based Priors}}. \emph{Empirical Methods in Natural Language Processing}, 2015, 5 pages (28\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Philip Resnik, and Jonathan Chang. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_nips_l2h.pdf}{Learning a Concept Hierarchy from Multi-labeled Documents}}. \emph{Neural Information Processing Systems}, 2014, 9 pages (25\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Jonathan Chang, and Philip Resnik. {\bf Tree-Based Label Dependency Topic Models}. \emph{NIPS Workshop on Topic Models: Computation, Application, and Evaluation}, 2013. \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, {\bf Jordan Boyd-Graber}, Nima Asadi, and \underline{Mohamad (Jude) Alkhouja}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2012_www_mrlda.pdf}{{Mr. LDA}: A Flexible Large Scale Topic Modeling Package using Variational Inference in MapReduce}}. \emph{ACM International Conference on World Wide Web}, 2012, 10 pages (12\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, and \underline{Brianna Satinoff}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/itm.pdf}{Interactive Topic Modeling}}. \emph{Association for Computational Linguistics}, 2011, 10 pages (25\% Acceptance Rate). \item Jonathan Chang, {\bf Jordan Boyd-Graber}, and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/kdd2009.pdf}{Connections between the Lines: Augmenting Social Networks with Text}}. \emph{Knowledge Discovery and Data Mining}, 2009, 9 pages (9\% Acceptance Rate). \item Jonathan Chang, {\bf Jordan Boyd-Graber}, and David M. Blei. {\bf Discovering social networks from free text}. \emph{3rd Annual Machine Learning Symposium}, 2008. \end{enumerate} } \headedsection{{\bf Deep Learning}}{}{ \begin{enumerate} \item Benjamin B\"orschinger, {\bf Jordan Boyd-Graber}, Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Michelle Chen Huebscher, Wojciech Gajewski, Yannic Kilcher, Rodrigo Nogueira, and Lierni Sestorain Saralegu. {\bf \href{https://arxiv.org/abs/1911.04156}{Meta Answering for Machine Reading}}. \emph{ArXiv}, Preprint, 10 pages. \item Pedro Rodriguez, Shi Feng, Mohit Iyyer, He He, and {\bf Jordan Boyd-Graber}. {\bf \href{https://arxiv.org/abs/1904.04792}{Quizbowl: The Case for Incremental Question Answering}}. \emph{ArXiv}, Preprint, 55 pages. \item Ishani Mondal, Shwetha S, Anandhavelu Natarajan, Aparna Garimella, Sambaran Bandyopadhyay, and Jordan Lee Boyd-Graber. {\bf Presentations by the People, for the People: Harnessing LLMs for Generating Persona-Aware Slides from Documents}. \emph{European Association for Computational Linguistics}, 2024 (21\% Acceptance Rate). \item Zongxia Li, Andrew Mao, Daniel Kofi Stephens, Pranav Goel, Emily Walpole, Juan Francisco Fung, Alden Dima, and Jordan Lee Boyd-Graber. {\bf TENOR: Topic Enabled Neural Organization and Recommendation: Evaluating Topic Models in Task Based Settings}. \emph{European Association for Computational Linguistics}, 2024 (21\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, Patrick Xia, Chandler May, Benjamin Van Durme, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_acl_alcoref.pdf}{Adapting Coreference Resolution Models through Active Learning}}. \emph{Association for Computational Linguistics}, 2022, 9 pages (21\% Acceptance Rate). \item Yoshinari Fujinuma, {\bf Jordan Boyd-Graber}, and Katharina Kann. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_acl_multilingbert.pdf}{How Does Multilingual Pretraining Affect Cross-Lingual Transferability?}}. \emph{Association for Computational Linguistics}, 2022, 9 pages (21\% Acceptance Rate). \item \underline{\href{https://noviscl.github.io/}{Chenglei Si}}, Chen Zhao, Sewon Min, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_emnlp_calibration.pdf}{Re-Examining Calibration: The Case of Question Answering}}. \emph{Findings of Empirical Methods in Natural Language Processing}, 2022, 9 pages. \item \underline{\href{https://csel.cs.colorado.edu/~fegu1724/}{Fenfei Guo}}, Chen Zhang, Zhirui Zhang, Qixin He, Kejun Zhang, Jun Xie, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_acl_ast.pdf}{Automatic Song Translation for Tonal Languages}}. \emph{Findings of the Association for Computational Linguistics}, 2022, 9 pages (31\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, Chenyan Xiong, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_emnlp_weak_dpr.pdf}{Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation}}. \emph{Empirical Methods in Natural Language Processing}, 2021, 11 pages (26\% Acceptance Rate). \item \underline{\href{https://noviscl.github.io/}{Chenglei Si}}, \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_emnlp_answer_equiv.pdf}{What's in a Name? Answer Equivalence For Open-Domain Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2021, 6 pages (18\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, Chenyan Xiong, Hal {Daum\'{e} III}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_naacl_multi_ance.pdf}{Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval}}. \emph{North American Association for Computational Linguistics}, 2021, 6 pages (23\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, Chenyan Xiong, Xin Qian, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_www_delft.pdf}{Complex Factoid Question Answering with a Free-Text Knowledge Graph}}. \emph{ACM International Conference on World Wide Web}, 2020, 11 pages (19.2\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, \underline{\href{http://akkikiki.github.io/about/}{Yoshinari Fujinuma}}, Michael J. Paul, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_acl_refine.pdf}{Why Overfitting Isn't Always Bad: Retrofitting Cross-Lingual Word Embeddings to Dictionaries}}. \emph{Association for Computational Linguistics}, 2020 (17.6\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, \underline{\href{http://akkikiki.github.io/about/}{Yoshinari Fujinuma}}, and {\bf Jordan Boyd-Graber}. {\bf \href{https://arxiv.org/abs/1812.09617}{Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification}}. \emph{Association for the Advancement of Artificial Intelligence}, 2020, 9 pages (20.6\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, Hsuan-Tien Lin, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_emnlp_alps.pdf}{Cold-start Active Learning through Self-Supervised Language Modeling}}. \emph{Empirical Methods in Natural Language Processing}, 2020, 9 pages (25\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, Benjamin {Van Durme}, Leah Findlater, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_emnlp_clime.pdf}{Interactive Refinement of Cross-Lingual Word Embeddings}}. \emph{Empirical Methods in Natural Language Processing}, 2020, 9 pages (25\% Acceptance Rate). \item \underline{\href{https://csel.cs.colorado.edu/~fegu1724/}{Fenfei Guo}}, {\bf Jordan Boyd-Graber}, Mohit Iyyer, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_lrec_sense.pdf}{Which Evaluations Uncover Sense Representations that Actually Make Sense?}}. \emph{Linguistic Resources and Evaluation Conference}, 2020, 10 pages. \item Francesco Saverio Varini, {\bf Jordan Boyd-Graber}, Massimiliano Ciaramita, and Markus Leippold. {\bf ClimaText: A Dataset for Climate Change Topic Detection}. \emph{NeurIPS Workshop on Tackling Climate Change with Machine Learning}, 2020. \item \underline{\href{http://akkikiki.github.io/about/}{Yoshinari Fujinuma}}, Michael Paul, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_modularity.pdf}{A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity}}. \emph{Association for Computational Linguistics}, 2019, 10 pages (26\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, Keyulu Xu, Ken-ichi Kawarabayashi, Stefanie Jegelka, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_clwe.pdf}{Are Girls Neko or Sh{\=o}jo? {C}ross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization}}. \emph{Association for Computational Linguistics}, 2019 (18.3\% Acceptance Rate). \item \underline{\href{http://www.ericswallace.com/}{Eric Wallace}}, \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_flipside.pdf}{Misleading Failures of Partial-input Baselines}}. \emph{Association for Computational Linguistics}, 2019, 6 pages (18\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~elgohary/}{Ahmed Elgohary Ghoneim}}, \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_emnlp_sequentialqa.pdf}{Can You Unpack That? Learning to Rewrite Questions-in-Context}}. \emph{Empirical Methods in Natural Language Processing}, 2019, 6 pages. \item \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, \underline{\href{http://akkikiki.github.io/about/}{Yoshinari Fujinuma}}, and {\bf Jordan Boyd-Graber}. {\bf Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification}. \emph{ACL Workshop on Deep Learning Approaches for Low-Resource Natural Language Processing}, 2018, 6 pages. \item \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, \underline{\href{http://www.ericswallace.com/}{Eric Wallace}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://aclweb.org/anthology/W18-5416}{Interpreting Neural Networks with Nearest Neighbors}}. \emph{EMNLP Workshop on BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP}, 2018, 7 pages. \item \underline{\href{http://www.cs.umd.edu/~elgohary/}{Ahmed Elgohary Ghoneim}}, \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_emnlp_linked.pdf}{Dataset and Baselines for Sequential Open-Domain Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2018, 6 pages (23\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, \underline{\href{http://www.ericswallace.com/}{Eric Wallace}}, Alvin Grissom II, \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}, Mohit Iyyer, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_emnlp_rs.pdf}{Pathologies of Neural Models Make Interpretation Difficult}}. \emph{Empirical Methods in Natural Language Processing}, 2018, 9 pages (26\% Acceptance Rate). \item Mohit Iyyer, Varun Manjunatha, {\bf Jordan Boyd-Graber}, and Larry Davis. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_naacl_colorization.pdf}{Learning to Color from Language}}. \emph{North American Association for Computational Linguistics}, 2018, 6 pages (29\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Varun Manjunatha, Anupam Guha, Yogarshi Vyas, {\bf Jordan Boyd-Graber}, Hal {Daum\'{e} III}, and Larry Davis. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_cvpr_comics.pdf}{The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives}}. \emph{Computer Vision and Pattern Recognition}, 2017, 10 pages (30\% Acceptance Rate). \item Hadi Amiri, Philip Resnik, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_acl_context_ae.pdf}{Learning Text Pair Similarity with Context-sensitive Autoencoders}}. \emph{Association for Computational Linguistics}, 2016 (28\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Anupam Guha, Snigdha Chaturvedi, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_relationships.pdf}{Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships}}. \emph{North American Association for Computational Linguistics}, 2016, 11 pages (24\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Varun Manjunatha, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_acl_dan.pdf}{Deep Unordered Composition Rivals Syntactic Methods for Text Classification}}. \emph{Association for Computational Linguistics}, 2015, 11 pages (25\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, \underline{\href{https://hhexiy.github.io/}{He He}}, and Hal {Daum\'{e} III}. {\bf Interactive Incremental Question Answering}. \emph{Neural Information Processing Systems}, 2015. \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Peter Enns, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_acl_rnn_ideology.pdf}{Political Ideology Detection Using Recursive Neural Networks}}. \emph{Association for Computational Linguistics}, 2014, 10 pages (26\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, {\bf Jordan Boyd-Graber}, Leonardo Claudino, Richard Socher, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_emnlp_qb_rnn.pdf}{A Neural Network for Factoid Question Answering over Paragraphs}}. \emph{Empirical Methods in Natural Language Processing}, 2014, 12 pages (26\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf Generating Sentences from Semantic Vector Space Representations}. \emph{NIPS Workshop on Learning Semantics}, 2014. \end{enumerate} } \headedsection{{\bf Digital Humanities}}{}{ \begin{enumerate} \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Anupam Guha, Snigdha Chaturvedi, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_relationships.pdf}{Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships}}. \emph{North American Association for Computational Linguistics}, 2016, 11 pages (24\% Acceptance Rate). \item Clay Templeton, Travis Brown, Sayan Battacharyya, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/slda_civil_war.pdf}{Mining the Dispatch under Supervision: Using Casualty Counts to Guide Topics from the Richmond Daily Dispatch Corpus}}. \emph{Chicago Colloquium on Digital Humanities and Computer Science}, 2011, 7 pages. \end{enumerate} } \headedsection{{\bf Empirical Human Data Collection}}{}{ \begin{enumerate} \item Benjamin B\"orschinger, {\bf Jordan Boyd-Graber}, Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Michelle Chen Huebscher, Wojciech Gajewski, Yannic Kilcher, Rodrigo Nogueira, and Lierni Sestorain Saralegu. {\bf \href{https://arxiv.org/abs/1911.04156}{Meta Answering for Machine Reading}}. \emph{ArXiv}, Preprint, 10 pages. \item Pedro Rodriguez, Shi Feng, Mohit Iyyer, He He, and {\bf Jordan Boyd-Graber}. {\bf \href{https://arxiv.org/abs/1904.04792}{Quizbowl: The Case for Incremental Question Answering}}. \emph{ArXiv}, Preprint, 55 pages. \item Ishani Mondal, Shwetha S, Anandhavelu Natarajan, Aparna Garimella, Sambaran Bandyopadhyay, and Jordan Lee Boyd-Graber. {\bf Presentations by the People, for the People: Harnessing LLMs for Generating Persona-Aware Slides from Documents}. \emph{European Association for Computational Linguistics}, 2024 (21\% Acceptance Rate). \item Zongxia Li, Andrew Mao, Daniel Kofi Stephens, Pranav Goel, Emily Walpole, Juan Francisco Fung, Alden Dima, and Jordan Lee Boyd-Graber. {\bf TENOR: Topic Enabled Neural Organization and Recommendation: Evaluating Topic Models in Task Based Settings}. \emph{European Association for Computational Linguistics}, 2024 (21\% Acceptance Rate). \item Chenglei Si, Navita Goyal, Tongshuang Wu, Chen Zhao, Shi Feng, Hal Daum\'{e} {III}, and Jordan Lee Boyd-Graber. {\bf Large Language Models Help Humans Verify Truthfulness---Except When They Are Convincingly Wrong}. \emph{North American Association for Computational Linguistics}, 2024. \item Srikanth, Neha Pundlik, Rupak Sarkar, Mane, Heran Y., Aparicio, Elizabeth M., Nguyen, Quynh C., Rachel Rudinger, and {\bf Jordan Boyd-Graber}. {\bf Large Language Models Help Humans Verify Truthfulness---Except When They Are Convincingly Wrong}. \emph{North American Association for Computational Linguistics}, 2024. \item Program Chairs' Report on Peer Review at ACL 2023. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2023_acl_peer_review_report.pdf}{Anna Rogers, Marzena Karpinska, Jordan Boyd-Graber, Naoaki Okazaki}}. \emph{Association for Computational Linguistics}, 2023, 33 pages. \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, Patrick Xia, Chandler May, Benjamin Van Durme, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_acl_alcoref.pdf}{Adapting Coreference Resolution Models through Active Learning}}. \emph{Association for Computational Linguistics}, 2022, 9 pages (21\% Acceptance Rate). \item Shi Feng and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_emnlp_augment.pdf}{Learning to Explain Selectively: A Case Study on Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2022, 9 pages. \item Wanrong He, \underline{Andrew Mao}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_emnlp_cheaters.pdf}{Cheater's Bowl: Human vs. Computer Search Strategies for Open-Domain QA}}. \emph{Findings of Empirical Methods in Natural Language Processing}, 2022, 9 pages. \item \underline{\href{https://csel.cs.colorado.edu/~fegu1724/}{Fenfei Guo}}, Chen Zhang, Zhirui Zhang, Qixin He, Kejun Zhang, Jun Xie, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_acl_ast.pdf}{Automatic Song Translation for Tonal Languages}}. \emph{Findings of the Association for Computational Linguistics}, 2022, 9 pages (31\% Acceptance Rate). \item \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}, Joe Barrow, Alexander Hoyle, John P. Lalor, Robin Jia, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_acl_leaderboard.pdf}{Evaluation Examples Are Not Equally Informative: How Should That Change NLP Leaderboards?}}. \emph{Association for Computational Linguistics}, 2021, 9 pages (21\% Acceptance Rate). \item \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_emnlp_paradigms.pdf}{Evaluation Paradigms in Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2021, 5 pages (18\% Acceptance Rate). \item Maharshi Gor, Kellie Webster, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_emnlp_qa_fairness.pdf}{Toward Deconfounding the Influence of Subject's Demographic Characteristics in Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2021, 9 pages (26\% Acceptance Rate). \item \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, Viktor Hangya, {\bf Jordan Boyd-Graber}, and Alexander Fraser. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_emnlp_adaptation.pdf}{Adapting Entities across Languages and Cultures}}. \emph{Findings of Empirical Methods in Natural Language Processing}, 2021, 5 pages (37\% Acceptance Rate). \item Alexander Hoyle, Pranav Goel, \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, Andrew Hian-Cheong, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_neurips_incoherence.pdf}{Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence}}. \emph{Neural Information Processing Systems}, 2021, 10 pages (26\% Acceptance Rate). \item Julian Martin Eisenschlos, Bhuwan Dhingra, Jannis Bulian, Benjamin B\"orschinger, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_naacl_fm2.pdf}{Fool Me Twice: Entailment from Wikipedia Gamification}}. \emph{North American Association for Computational Linguistics}, 2021, 10 pages (28\% Acceptance Rate). \item \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, Benny Cheng, \underline{\href{http://www.cs.umd.edu/~elgohary/}{Ahmed Elgohary Ghoneim}}, Joe Barrow, Cristian Danescu-Niculescu-Mizil, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_acl_diplomacy.pdf}{It Takes Two to Lie: One to Lie and One to Listen}}. \emph{Association for Computational Linguistics}, 2020 (25.4\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, Hsuan-Tien Lin, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_emnlp_alps.pdf}{Cold-start Active Learning through Self-Supervised Language Modeling}}. \emph{Empirical Methods in Natural Language Processing}, 2020, 9 pages (25\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, Benjamin {Van Durme}, Leah Findlater, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_emnlp_clime.pdf}{Interactive Refinement of Cross-Lingual Word Embeddings}}. \emph{Empirical Methods in Natural Language Processing}, 2020, 9 pages (25\% Acceptance Rate). \item \underline{\href{https://csel.cs.colorado.edu/~fegu1724/}{Fenfei Guo}}, {\bf Jordan Boyd-Graber}, Mohit Iyyer, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_lrec_sense.pdf}{Which Evaluations Uncover Sense Representations that Actually Make Sense?}}. \emph{Linguistic Resources and Evaluation Conference}, 2020, 10 pages. \item Diggelmann, Thomas, Boyd-Graber, Jordan, Bulian, Jannis, Ciaramita, Massimiliano, and Leippold, Markus. {\bf \href{https://research.google/pubs/pub50541/}{CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims}}. \emph{NIPS Workshop on Tackling Climate Change with Machine Learning}, 2020. \item \underline{\href{http://www.cs.umd.edu/~elgohary/}{Ahmed Elgohary Ghoneim}}, \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_emnlp_sequentialqa.pdf}{Can You Unpack That? Learning to Rewrite Questions-in-Context}}. \emph{Empirical Methods in Natural Language Processing}, 2019, 6 pages. \item \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_iui_augment.pdf}{What AI can do for me: Evaluating Machine Learning Interpretations in Cooperative Play}}. \emph{Intelligent User Interfaces}, 2019 (25\% Acceptance Rate). \item \underline{\href{http://www.ericswallace.com/}{Eric Wallace}}, \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}, \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, Ikuya Yamada, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_tacl_trick.pdf}{Trick Me If You Can: Human-in-the-loop Generation of Adversarial Question Answering Examples}}. \emph{Transactions of the Association for Computational Linguistics}, 2019, 14 pages. \item \underline{\href{http://www.ericswallace.com/}{Eric Wallace}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://aclweb.org/anthology/P18-3018}{Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions}}. \emph{ACL Student Research Workshop}, 2018, 6 pages. \item \underline{\href{http://www.cs.umd.edu/~elgohary/}{Ahmed Elgohary Ghoneim}}, \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_emnlp_linked.pdf}{Dataset and Baselines for Sequential Open-Domain Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2018, 6 pages (23\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, \underline{\href{http://www.ericswallace.com/}{Eric Wallace}}, Alvin Grissom II, \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}, Mohit Iyyer, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_emnlp_rs.pdf}{Pathologies of Neural Models Make Interpretation Difficult}}. \emph{Empirical Methods in Natural Language Processing}, 2018, 9 pages (26\% Acceptance Rate). \item Paul Felt, Eric Ringger, Kevin Seppi, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_coling_measurements.pdf}{Learning from Measurements in Crowdsourcing Models: Inferring Ground Truth from Diverse Annotation Types}}. \emph{International Conference on Computational Linguistics}, 2018, 10 pages (37\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, Benjamin {Van Durme}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_neurips_mtanchor.pdf}{Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages}}. \emph{Neural Information Processing Systems}, 2018, 10 pages (21\% Acceptance Rate). \item Mohit Iyyer, Varun Manjunatha, {\bf Jordan Boyd-Graber}, and Larry Davis. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_naacl_colorization.pdf}{Learning to Color from Language}}. \emph{North American Association for Computational Linguistics}, 2018, 6 pages (29\% Acceptance Rate). \item Shudong Hao, Michael J. Paul, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_naacl_mltm_eval.pdf}{Lessons from the Bible on Modern Topics: Multilingual Topic Model Evaluation on Low-Resource Languages}}. \emph{North American Association for Computational Linguistics}, 2018, 9 pages (35\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Varun Manjunatha, Anupam Guha, Yogarshi Vyas, {\bf Jordan Boyd-Graber}, Hal {Daum\'{e} III}, and Larry Davis. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_cvpr_comics.pdf}{The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives}}. \emph{Computer Vision and Pattern Recognition}, 2017, 10 pages (30\% Acceptance Rate). \item Tak Yeon Lee, \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Kevin Seppi, Niklas Elmqvist, {\bf Jordan Boyd-Graber}, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_ijhcs_human_touch.pdf}{The Human Touch: How Non-expert Users Perceive, Interpret, and Fix Topic Models}}. \emph{International Journal of Human-Computer Studies}, 2017, 27 pages. \item \underline{\href{https://www.ursinus.edu/live/profiles/3125-alvin-grissom-ii}{Alvin Grissom II}}, Naho Orita, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_conll_verbpred.pdf}{Incremental Prediction of Sentence-final Verbs}}. \emph{Conference on Computational Natural Language Learning}, 2016, 10 pages (20\% Acceptance Rate). \item \underline{\href{https://hhexiy.github.io/}{He He}}, {\bf Jordan Boyd-Graber}, Kevin Kwok, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_icml_opponent.pdf}{Opponent Modeling in Deep Reinforcement Learning}}. \emph{International Conference on Machine Learning}, 2016, 10 pages (24\% Acceptance Rate). \item Anupam Guha, \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_paintings.pdf}{A Distorted Skull Lies in the Bottom Center: Identifying Paintings from Text Descriptions}}. \emph{NAACL Human-Computer Question Answering Workshop}, 2016. \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Anupam Guha, Snigdha Chaturvedi, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_relationships.pdf}{Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships}}. \emph{North American Association for Computational Linguistics}, 2016, 11 pages (24\% Acceptance Rate). \item \underline{\href{https://hhexiy.github.io/}{He He}}, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_interpretese.pdf}{Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation}}. \emph{North American Association for Computational Linguistics}, 2016, 6 pages (29\% Acceptance Rate). \item Vlad Niculae, Srijan Kumar, {\bf Jordan Boyd-Graber}, and Cristian Danescu-Niculescu-Mizil. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_acl_diplomacy.pdf}{Linguistic Harbingers of Betrayal: A Case Study on an Online Strategy Game}}. \emph{Association for Computational Linguistics}, 2015, 10 pages (25\% Acceptance Rate). \item Paul Felt, Eric Ringger, {\bf Jordan Boyd-Graber}, and Kevin Seppi. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_conll_cslda.pdf}{Making the Most of Crowdsourced Document Annotations: Confused Supervised {LDA}}}. \emph{Conference on Computational Natural Language Learning}, 2015, 10 pages (30\% Acceptance Rate). \item Anupam Guha, \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Danny Bouman, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_naacl_qb_coref.pdf}{Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers}}. \emph{North American Association for Computational Linguistics}, 2015, 11 pages (26\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, David Mimno, and David Newman. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_book_chapter_care_and_feeding.pdf}{Care and Feeding of Topic Models: Problems, Diagnostics, and Improvements}}. \emph{Handbook of Mixed Membership Models and Their Applications}, 2014, 39 pages. \item {\bf Jordan Boyd-Graber}, \underline{Brianna Satinoff}, \underline{\href{https://hhexiy.github.io/}{He He}}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/qb_emnlp_2012.pdf}{Besting the Quiz Master: Crowdsourcing Incremental Classification Games}}. \emph{Empirical Methods in Natural Language Processing}, 2012, 12 pages (25\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}} and {\bf Jordan Boyd-Graber}. {\bf Suggesting Constraints for Interactive Topic Modeling}. \emph{ICML Workshop on Machine Learning in Human Computation and Crowdsourcing}, 2012. \item Clay Templeton, Kenneth R. Fleischmann, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/simulating_audiences.pdf}{Simulating Audiences: Automating Analysis of Values, Attitudes, and Sentiment}}. \emph{IEEE International Conference on Social Computing}, 2011, 4 pages (10\% Acceptance Rate). \item Sonya S. Nikolova, {\bf Jordan Boyd-Graber}, and Christiane Fellbaum. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2011_book_chapter_evocation.pdf}{Collecting Semantic Similarity Ratings to Connect Concepts in Assistive Communication Tools}}. \emph{Modeling, Learning and Processing of Text Technological Data Structures}, 2011, 11 pages. \item {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2011_resources.pdf}{Linguistic Resource Creation in a Web 2.0 World}}. \emph{NSF Workshop on Collaborative Annotation}, 2011, 7 pages. \item \underline{Brianna Satinoff} and {\bf Jordan Boyd-Graber}. {\bf Trivial Classification: What features do humans use for classification?}. \emph{Workshop on Crowdsourcing Technologies for Language and Cognition Studies}, 2011. \item Clay Templeton, Kenneth R. Fleischmann, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/iconference-2011-comparing.pdf}{Comparing Values and Sentiment Using Mechanical Turk}}. \emph{iConference}, 2011, 2 pages. \item Kenneth R. Fleischmann, Clay Templeton, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/iconference-2011-learning.pdf}{Modeling Diverse Standpoints in Text Classification: Learning to Be Human by Modeling Human Values}}. \emph{iConference}, 2011, 2 pages. \item Nitin Madnani, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/madnani-boyd-graber-turk-workshop.pdf}{Measuring Transitivity Using Untrained Annotators}}. \emph{Creating Speech and Language Data With Amazon's Mechanical Turk}, 2010, 6 pages. \item Jonathan Chang, {\bf Jordan Boyd-Graber}, Chong Wang, Sean Gerrish, and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/nips2009-rtl.pdf}{Reading Tea Leaves: How Humans Interpret Topic Models}}. \emph{Neural Information Processing Systems}, 2009, 9 pages (24\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, Christiane Fellbaum, Daniel Osherson, and Robert Schapire. {\bf \href{http://umiacs.umd.edu/~jbg//docs/jbg-jeju.pdf}{Adding Dense, Weighted, Connections to {WordNet}}}. \emph{Proceedings of the Global {WordNet} Conference}, 2006, 10 pages. \end{enumerate} } \headedsection{{\bf Fact Checking}}{}{ \begin{enumerate} \item Chenglei Si, Navita Goyal, Tongshuang Wu, Chen Zhao, Shi Feng, Hal Daum\'{e} {III}, and Jordan Lee Boyd-Graber. {\bf Large Language Models Help Humans Verify Truthfulness---Except When They Are Convincingly Wrong}. \emph{North American Association for Computational Linguistics}, 2024. \item Julian Martin Eisenschlos, Bhuwan Dhingra, Jannis Bulian, Benjamin B\"orschinger, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_naacl_fm2.pdf}{Fool Me Twice: Entailment from Wikipedia Gamification}}. \emph{North American Association for Computational Linguistics}, 2021, 10 pages (28\% Acceptance Rate). \item Diggelmann, Thomas, Boyd-Graber, Jordan, Bulian, Jannis, Ciaramita, Massimiliano, and Leippold, Markus. {\bf \href{https://research.google/pubs/pub50541/}{CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims}}. \emph{NIPS Workshop on Tackling Climate Change with Machine Learning}, 2020. \end{enumerate} } \headedsection{{\bf Human-Computer Interaction}}{}{ \begin{enumerate} \item Ishani Mondal, Shwetha S, Anandhavelu Natarajan, Aparna Garimella, Sambaran Bandyopadhyay, and Jordan Lee Boyd-Graber. {\bf Presentations by the People, for the People: Harnessing LLMs for Generating Persona-Aware Slides from Documents}. \emph{European Association for Computational Linguistics}, 2024 (21\% Acceptance Rate). \item Zongxia Li, Andrew Mao, Daniel Kofi Stephens, Pranav Goel, Emily Walpole, Juan Francisco Fung, Alden Dima, and Jordan Lee Boyd-Graber. {\bf TENOR: Topic Enabled Neural Organization and Recommendation: Evaluating Topic Models in Task Based Settings}. \emph{European Association for Computational Linguistics}, 2024 (21\% Acceptance Rate). \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, {\bf Jordan Boyd-Graber}, Ron Fan, Melissa Birchfield, Tongshuang Wu, Dan Weld, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_chi_explanation.pdf}{No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML}}. \emph{Computer-Human Interaction}, 2020 (24\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, Hsuan-Tien Lin, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_emnlp_alps.pdf}{Cold-start Active Learning through Self-Supervised Language Modeling}}. \emph{Empirical Methods in Natural Language Processing}, 2020, 9 pages (25\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, Benjamin {Van Durme}, Leah Findlater, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_emnlp_clime.pdf}{Interactive Refinement of Cross-Lingual Word Embeddings}}. \emph{Empirical Methods in Natural Language Processing}, 2020, 9 pages (25\% Acceptance Rate). \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Varun Kumar, {\bf Jordan Boyd-Graber}, Kevin Seppi, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_iui_control.pdf}{Digging into User Control: Perceptions of Adherence and Instability in Transparent Models}}. \emph{Intelligent User Interfaces}, 2020, 12 pages (23\% Acceptance Rate). \item Varun Kumar, \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Leah Findlater, Kevin Seppi, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_control.pdf}{Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models}}. \emph{Association for Computational Linguistics}, 2019, 6 pages (18\% Acceptance Rate). \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Varun Kumar, {\bf Jordan Boyd-Graber}, Kevin Seppi, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_iui_itm.pdf}{User-Centered Design and Evaluation of a Human-in-the-Loop Topic Modeling System}}. \emph{Intelligent User Interfaces}, 2018, 12 pages (23\% Acceptance Rate). \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Varun Kumar, {\bf Jordan Boyd-Graber}, Kevin Seppi, and Leah Findlater. {\bf \href{http://visualization.ischool.uw.edu/hci_uncertainty/papers/Paper11.pdf}{Accounting for Input Uncertainty in Human-in-the-Loop Systems}}. \emph{CHI 2017 Designing for Uncertainty Workshop}, 2017. \item Tak Yeon Lee, \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Kevin Seppi, Niklas Elmqvist, {\bf Jordan Boyd-Graber}, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_ijhcs_human_touch.pdf}{The Human Touch: How Non-expert Users Perceive, Interpret, and Fix Topic Models}}. \emph{International Journal of Human-Computer Studies}, 2017, 27 pages. \item {\bf Jordan Boyd-Graber}. {\bf Humans and Computers Working Together to Measure Machine Learning Interpretability}. \emph{The Bridge}, 2017, 5 pages. \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Tak Yeon Lee, \underline{\href{https://www.microsoft.com/en-us/research/people/fopoursa/}{Forough Poursabzi-Sangdeh}}, {\bf Jordan Boyd-Graber}, Kevin Seppi, Niklas Elmqvist, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_tacl_eval_tm_viz.pdf}{Evaluating Visual Representations for Topic Understanding and Their Effects on Manually Generated Labels}}. \emph{Transactions of the Association for Computational Linguistics}, 2017, 15 pages. \item \underline{\href{https://www.microsoft.com/en-us/research/people/fopoursa/}{Forough Poursabzi-Sangdeh}}, {\bf Jordan Boyd-Graber}, Leah Findlater, and Kevin Seppi. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_acl_doclabel.pdf}{ALTO: Active Learning with Topic Overviews for Speeding Label Induction and Document Labeling}}. \emph{Association for Computational Linguistics}, 2016 (28\% Acceptance Rate). \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Tak Yeon Lee, \underline{\href{https://www.microsoft.com/en-us/research/people/fopoursa/}{Forough Poursabzi-Sangdeh}}, {\bf Jordan Boyd-Graber}, Kevin Seppi, Niklas Elmqvist, and Leah Findlater. {\bf Human-Centered and Interactive: Expanding the Impact of Topic Models}. \emph{CHI Human Centred Machine Learning Workshop}, 2016. \item \underline{\href{https://hhexiy.github.io/}{He He}}, {\bf Jordan Boyd-Graber}, Kevin Kwok, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_icml_opponent.pdf}{Opponent Modeling in Deep Reinforcement Learning}}. \emph{International Conference on Machine Learning}, 2016, 10 pages (24\% Acceptance Rate). \item \underline{\href{https://www.microsoft.com/en-us/research/people/fopoursa/}{Forough Poursabzi-Sangdeh}} and {\bf Jordan Boyd-Graber}. {\bf Speeding Document Annotation with Topic Models}. \emph{NAACL Student Research Workshop}, 2015. \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Jason Chuang, \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, and Leah Findlater. {\bf Concurrent Visualization of Relationships between Words and Topics in Topic Models}. \emph{ACL Workshop on Workshop on Interactive Language Learning, Visualization, and Interfaces}, 2014. \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, Brianna Satinoff, and \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_mlj_itm.pdf}{Interactive Topic Modeling}}. \emph{Machine Learning}, 2014, 56 pages. \item Jason Chuang, John D. Wilkerson, Rebecca Weiss, Dustin Tingley, Brandon M. Stewart, Margaret E. Roberts, \underline{\href{https://www.microsoft.com/en-us/research/people/fopoursa/}{Forough Poursabzi-Sangdeh}}, Justin Grimmer, Leah Findlater, {\bf Jordan Boyd-Graber}, and Jeffrey Heer. {\bf Computer-Assisted Content Analysis: Topic Models for Exploring Multiple Subjective Interpretations}. \emph{NIPS Workshop on Human-Propelled Machine Learning}, 2014. \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_argviz.pdf}{Argviz: Interactive Visualization of Topic Dynamics in Multi-party Conversations}}. \emph{North American Association for Computational Linguistics}, 2013, 4 pages (50\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, \underline{Brianna Satinoff}, \underline{\href{https://hhexiy.github.io/}{He He}}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/qb_emnlp_2012.pdf}{Besting the Quiz Master: Crowdsourcing Incremental Classification Games}}. \emph{Empirical Methods in Natural Language Processing}, 2012, 12 pages (25\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}} and {\bf Jordan Boyd-Graber}. {\bf Suggesting Constraints for Interactive Topic Modeling}. \emph{ICML Workshop on Machine Learning in Human Computation and Crowdsourcing}, 2012. \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, and \underline{Brianna Satinoff}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/itm.pdf}{Interactive Topic Modeling}}. \emph{Association for Computational Linguistics}, 2011, 10 pages (25\% Acceptance Rate). \item \underline{Brianna Satinoff} and {\bf Jordan Boyd-Graber}. {\bf Trivial Classification: What features do humans use for classification?}. \emph{Workshop on Crowdsourcing Technologies for Language and Cognition Studies}, 2011. \item Sonya S. Nikolova, {\bf Jordan Boyd-Graber}, Christiane Fellbaum, and Perry Cook. {\bf \href{http://umiacs.umd.edu/~jbg//docs/evocation-viva.pdf}{Better Vocabularies for Assistive Communication Aids: Connecting Terms using Semantic Networks and Untrained Annotators}}. \emph{ACM Conference on Computers and Accessibility}, 2009, 8 pages (31\% Acceptance Rate). \item Xiaojuan Ma, {\bf Jordan Boyd-Graber}, Sonya S. Nikolova, and Perry Cook. {\bf \href{http://umiacs.umd.edu/~jbg//docs/image_icon.pdf}{Speaking Through Pictures: Images vs. Icons}}. \emph{ACM Conference on Computers and Accessibility}, 2009, 8 pages (31\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, Sonya S. Nikolova, Karyn A. Moffatt, Kenrick C. Kin, Joshua Y. Lee, Lester W. Mackey, Marilyn M. Tremaine, and Maria M. Klawe. {\bf \href{http://umiacs.umd.edu/~jbg//docs/paper673-boyd-graber.pdf}{Participatory design with proxies: {D}eveloping a desktop-{PDA} system to support people with aphasia}}. \emph{Computer-Human Interaction}, 2006, 10 pages (23\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Images}}{}{ \begin{enumerate} \item Mohit Iyyer, Varun Manjunatha, {\bf Jordan Boyd-Graber}, and Larry Davis. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_naacl_colorization.pdf}{Learning to Color from Language}}. \emph{North American Association for Computational Linguistics}, 2018, 6 pages (29\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Varun Manjunatha, Anupam Guha, Yogarshi Vyas, {\bf Jordan Boyd-Graber}, Hal {Daum\'{e} III}, and Larry Davis. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_cvpr_comics.pdf}{The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives}}. \emph{Computer Vision and Pattern Recognition}, 2017, 10 pages (30\% Acceptance Rate). \item Anupam Guha, \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_paintings.pdf}{A Distorted Skull Lies in the Bottom Center: Identifying Paintings from Text Descriptions}}. \emph{NAACL Human-Computer Question Answering Workshop}, 2016. \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, Sinead Williamson, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/mtibp_icml_2012.pdf}{Modeling Images using Transformed {I}ndian Buffet Processes}}. \emph{International Conference on Machine Learning}, 2012, 8 pages (27\% Acceptance Rate). \item Xiaojuan Ma, {\bf Jordan Boyd-Graber}, Sonya S. Nikolova, and Perry Cook. {\bf \href{http://umiacs.umd.edu/~jbg//docs/image_icon.pdf}{Speaking Through Pictures: Images vs. Icons}}. \emph{ACM Conference on Computers and Accessibility}, 2009, 8 pages (31\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Interpretability}}{}{ \begin{enumerate} \item Shi Feng and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_emnlp_augment.pdf}{Learning to Explain Selectively: A Case Study on Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2022, 9 pages. \item Wanrong He, \underline{Andrew Mao}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_emnlp_cheaters.pdf}{Cheater's Bowl: Human vs. Computer Search Strategies for Open-Domain QA}}. \emph{Findings of Empirical Methods in Natural Language Processing}, 2022, 9 pages. \item Alexander Hoyle, Pranav Goel, \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, Andrew Hian-Cheong, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_neurips_incoherence.pdf}{Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence}}. \emph{Neural Information Processing Systems}, 2021, 10 pages (26\% Acceptance Rate). \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, {\bf Jordan Boyd-Graber}, Ron Fan, Melissa Birchfield, Tongshuang Wu, Dan Weld, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_chi_explanation.pdf}{No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML}}. \emph{Computer-Human Interaction}, 2020 (24\% Acceptance Rate). \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Varun Kumar, {\bf Jordan Boyd-Graber}, Kevin Seppi, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_iui_control.pdf}{Digging into User Control: Perceptions of Adherence and Instability in Transparent Models}}. \emph{Intelligent User Interfaces}, 2020, 12 pages (23\% Acceptance Rate). \item \underline{\href{https://csel.cs.colorado.edu/~fegu1724/}{Fenfei Guo}}, {\bf Jordan Boyd-Graber}, Mohit Iyyer, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_lrec_sense.pdf}{Which Evaluations Uncover Sense Representations that Actually Make Sense?}}. \emph{Linguistic Resources and Evaluation Conference}, 2020, 10 pages. \item \underline{\href{http://www.ericswallace.com/}{Eric Wallace}}, \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_flipside.pdf}{Misleading Failures of Partial-input Baselines}}. \emph{Association for Computational Linguistics}, 2019, 6 pages (18\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_iui_augment.pdf}{What AI can do for me: Evaluating Machine Learning Interpretations in Cooperative Play}}. \emph{Intelligent User Interfaces}, 2019 (25\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, \underline{\href{http://www.ericswallace.com/}{Eric Wallace}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://aclweb.org/anthology/W18-5416}{Interpreting Neural Networks with Nearest Neighbors}}. \emph{EMNLP Workshop on BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP}, 2018, 7 pages. \item \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, \underline{\href{http://www.ericswallace.com/}{Eric Wallace}}, Alvin Grissom II, \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}, Mohit Iyyer, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_emnlp_rs.pdf}{Pathologies of Neural Models Make Interpretation Difficult}}. \emph{Empirical Methods in Natural Language Processing}, 2018, 9 pages (26\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}. {\bf Humans and Computers Working Together to Measure Machine Learning Interpretability}. \emph{The Bridge}, 2017, 5 pages. \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, Brianna Satinoff, and \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_mlj_itm.pdf}{Interactive Topic Modeling}}. \emph{Machine Learning}, 2014, 56 pages. \item Jonathan Chang, {\bf Jordan Boyd-Graber}, Chong Wang, Sean Gerrish, and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/nips2009-rtl.pdf}{Reading Tea Leaves: How Humans Interpret Topic Models}}. \emph{Neural Information Processing Systems}, 2009, 9 pages (24\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Large Language Models (or, more correctly, Muppet Models)}}{}{ \begin{enumerate} \item Ishani Mondal, Shwetha S, Anandhavelu Natarajan, Aparna Garimella, Sambaran Bandyopadhyay, and Jordan Lee Boyd-Graber. {\bf Presentations by the People, for the People: Harnessing LLMs for Generating Persona-Aware Slides from Documents}. \emph{European Association for Computational Linguistics}, 2024 (21\% Acceptance Rate). \item Chenglei Si, Navita Goyal, Tongshuang Wu, Chen Zhao, Shi Feng, Hal Daum\'{e} {III}, and Jordan Lee Boyd-Graber. {\bf Large Language Models Help Humans Verify Truthfulness---Except When They Are Convincingly Wrong}. \emph{North American Association for Computational Linguistics}, 2024. \item Srikanth, Neha Pundlik, Rupak Sarkar, Mane, Heran Y., Aparicio, Elizabeth M., Nguyen, Quynh C., Rachel Rudinger, and {\bf Jordan Boyd-Graber}. {\bf Large Language Models Help Humans Verify Truthfulness---Except When They Are Convincingly Wrong}. \emph{North American Association for Computational Linguistics}, 2024. \item \underline{\href{https://noviscl.github.io/}{Chenglei Si}}, Weijia Shi, Chen Zhao, Luke Zettlemoyer, and Jordan Lee Boyd-Graber. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2023_findings_more.pdf}{Getting \underline{MoRE} out of \underline{M}ixture \underline{o}f Language Model \underline{R}easoning \underline{E}xperts}}. \emph{Findings of Empirical Methods in Natural Language Processing}, 2023 (45\% Acceptance Rate). \item \underline{\href{https://noviscl.github.io/}{Chenglei Si}}, Zhe Gan, Zhengyuan Yang, Shuohang Wang, Jianfeng Wang, {\bf Jordan Boyd-Graber}, and Lijuan Wang. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2023_iclr_reliable.pdf}{Prompting GPT-3 To Be Reliable}}. \emph{International Conference on Learning Representations}, 2023. \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, Hsuan-Tien Lin, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_emnlp_alps.pdf}{Cold-start Active Learning through Self-Supervised Language Modeling}}. \emph{Empirical Methods in Natural Language Processing}, 2020, 9 pages (25\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Lexical Semantics}}{}{ \begin{enumerate} \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, Benjamin {Van Durme}, Leah Findlater, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_emnlp_clime.pdf}{Interactive Refinement of Cross-Lingual Word Embeddings}}. \emph{Empirical Methods in Natural Language Processing}, 2020, 9 pages (25\% Acceptance Rate). \item \underline{\href{https://csel.cs.colorado.edu/~fegu1724/}{Fenfei Guo}}, {\bf Jordan Boyd-Graber}, Mohit Iyyer, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_lrec_sense.pdf}{Which Evaluations Uncover Sense Representations that Actually Make Sense?}}. \emph{Linguistic Resources and Evaluation Conference}, 2020, 10 pages. \item Daniel Peterson, {\bf Jordan Boyd-Graber}, Martha Palmer, and Daisuke Kawahara. {\bf \href{https://aclanthology.org/S16-2012/}{Leveraging {V}erb{N}et to build Corpus-Specific Verb Clusters}}. \emph{Proceedings of the Fifth Joint Conference on Lexical and Computational Semantics}, 2016, 5 pages. \item Sonya S. Nikolova, {\bf Jordan Boyd-Graber}, and Christiane Fellbaum. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2011_book_chapter_evocation.pdf}{Collecting Semantic Similarity Ratings to Connect Concepts in Assistive Communication Tools}}. \emph{Modeling, Learning and Processing of Text Technological Data Structures}, 2011, 11 pages. \item {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2011_resources.pdf}{Linguistic Resource Creation in a Web 2.0 World}}. \emph{NSF Workshop on Collaborative Annotation}, 2011, 7 pages. \item {\bf Jordan Boyd-Graber} and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/jbg-SEMEVAL07.pdf}{{PUTOP}: {T}urning Predominant Senses into a Topic Model for {WSD}}}. \emph{4th International Workshop on Semantic Evaluations}, 2007, 5 pages. \item {\bf Jordan Boyd-Graber}, David M. Blei, and Xiaojin Zhu. {\bf \href{http://umiacs.umd.edu/~jbg//docs/jbg-EMNLP07.pdf}{A Topic Model for Word Sense Disambiguation}}. \emph{Empirical Methods in Natural Language Processing}, 2007, 10 pages (27\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, Christiane Fellbaum, Daniel Osherson, and Robert Schapire. {\bf \href{http://umiacs.umd.edu/~jbg//docs/jbg-jeju.pdf}{Adding Dense, Weighted, Connections to {WordNet}}}. \emph{Proceedings of the Global {WordNet} Conference}, 2006, 10 pages. \end{enumerate} } \headedsection{{\bf MCMC Inference}}{}{ \begin{enumerate} \item Varun Kumar, \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Leah Findlater, Kevin Seppi, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_control.pdf}{Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models}}. \emph{Association for Computational Linguistics}, 2019, 6 pages (18\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_emnlp_mtm.pdf}{A Multilingual Topic Model for Learning Weighted Topic Links Across Incomparable Corpora}}. \emph{Empirical Methods in Natural Language Processing}, 2019, 6 pages. \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_emnlp_tree_prior.pdf}{Adapting Topic Models using Lexical Associations with Tree Priors}}. \emph{Empirical Methods in Natural Language Processing}, 2017, 6 pages (18\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_acl_docblock.pdf}{A Discriminative Topic Model using Document Network Structure}}. \emph{Association for Computational Linguistics}, 2016, 10 pages (28\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf Birds of a Feather in the Same Nest: A Discriminative Topic Model using Block-based Priors}. \emph{Mid-Atlantic Student Colloquium on Speech, Language, and Learning}, 2016. \item Md Arafat Sultan, {\bf Jordan Boyd-Graber}, and Tamara Sumner. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_sts.pdf}{Bayesian Supervised Domain Adaptation for Short Text Similarity}}. \emph{North American Association for Computational Linguistics}, 2016, 11 pages (24\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Philip Resnik, and Kristina Miler. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_acl_teaparty.pdf}{Tea Party in the House: A Hierarchical Ideal Point Topic Model and Its Application to Republican Legislators in the 112th Congress}}. \emph{Association for Computational Linguistics}, 2015, 11 pages (25\% Acceptance Rate). \item Paul Felt, Eric Ringger, {\bf Jordan Boyd-Graber}, and Kevin Seppi. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_conll_cslda.pdf}{Making the Most of Crowdsourced Document Annotations: Confused Supervised {LDA}}}. \emph{Conference on Computational Natural Language Learning}, 2015, 10 pages (30\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_emnlp_hinge_link.pdf}{Birds of a Feather Linked Together: A Discriminative Topic Model using Link-based Priors}}. \emph{Empirical Methods in Natural Language Processing}, 2015, 5 pages (28\% Acceptance Rate). \item Yi Yang, Doug Downey, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_emnlp_fast_priors.pdf}{Efficient Methods for Incorporating Knowledge into Topic Models}}. \emph{Empirical Methods in Natural Language Processing}, 2015, 9 pages (24\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, Vlad Eidelman, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_acl_ptlda_mt.pdf}{Polylingual Tree-Based Topic Models for Translation Domain Adaptation}}. \emph{Association for Computational Linguistics}, 2014, 11 pages (26\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Philip Resnik, and Jonathan Chang. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_nips_l2h.pdf}{Learning a Concept Hierarchy from Multi-labeled Documents}}. \emph{Neural Information Processing Systems}, 2014, 9 pages (25\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Jonathan Chang, and Philip Resnik. {\bf Tree-Based Label Dependency Topic Models}. \emph{NIPS Workshop on Topic Models: Computation, Application, and Evaluation}, 2013. \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, Hal {Daum\'{e} III}, and Z. Irene Ying. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_coalescent.pdf}{Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent}}. \emph{Neural Information Processing Systems}, 2013, 9 pages (25\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/acl_2012_fttm.pdf}{Efficient Tree-Based Topic Modeling}}. \emph{Association for Computational Linguistics}, 2012, 5 pages (21\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, Sinead Williamson, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/mtibp_icml_2012.pdf}{Modeling Images using Transformed {I}ndian Buffet Processes}}. \emph{International Conference on Machine Learning}, 2012, 8 pages (27\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}} and {\bf Jordan Boyd-Graber}. {\bf Bayesian Hierarchical Clustering with Beta Coalescents}. \emph{Mid-Atlantic Student Colloquium on Speech, Language, and Learning}, 2012. \end{enumerate} } \headedsection{{\bf Machine Translation}}{}{ \begin{enumerate} \item \underline{\href{https://h-j-han.github.io/}{HyoJung Han}}, Marine Carpuat, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2023_emnlp_explicitation.pdf}{Automatic Explicitation to Bridge the Background Knowledge Gap in Translation and its Evaluation with Multilingual QA}}. \emph{Empirical Methods in Natural Language Processing}, 2023, 9 pages (23\% Acceptance Rate). \item Sander V Schulhoff, Jeremy Pinto, Anaum Khan, Louis-François Bouchard, \underline{\href{https://noviscl.github.io/}{Chenglei Si}}, Jordan Lee Boyd-Graber, Svetlina Anati, Valen Tagliabue, Anson Liu Kost, and Christopher R Carnahan. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2023_emnlp_hackaprompt.pdf}{Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs Through a Global Prompt Hacking Competition}}. \emph{Empirical Methods in Natural Language Processing}, 2023, 9 pages (23\% Acceptance Rate). \item \underline{\href{http://yysung.github.io/}{Yoo Yeon Sung}}, Naeemul Hassan, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2023_emnlp_videoheadline.pdf}{Not all Fake News is Written: A Dataset and Analysis of Misleading Video Headlines}}. \emph{Empirical Methods in Natural Language Processing}, 2023, 9 pages (23\% Acceptance Rate). \item \underline{\href{https://h-j-han.github.io/}{HyoJung Han}}, Marine Carpuat, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_emnlp_simqa.pdf}{SimQA: Detecting Simultaneous MT Errors through Word-by-Word Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2022, 9 pages. \item Peter Jansen and {\bf Jordan Boyd-Graber}. {\bf \href{https://arxiv.org/abs/2107.08146}{Picard understanding Darmok: A Dataset and Model for Metaphor-Rich Translation in a Constructed Language}}. \emph{Figurative Language Workshop 2022 @EMNLP}, 2022. \item \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, Viktor Hangya, {\bf Jordan Boyd-Graber}, and Alexander Fraser. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_emnlp_adaptation.pdf}{Adapting Entities across Languages and Cultures}}. \emph{Findings of Empirical Methods in Natural Language Processing}, 2021, 5 pages (37\% Acceptance Rate). \item Wenyan Li, Alvin {Grissom II}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_findings_verbs.pdf}{An Attentive Recurrent Model for Incremental Prediction of Sentence-final Verbs}}. \emph{Findings of EMNLP}, 2020, 9 pages. \item Tianze Shi, \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, {\bf Jordan Boyd-Graber}, Hal {Daum\'{e} III}, and Lillian Lee. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_findings_qalign.pdf}{On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries}}. \emph{Findings of EMNLP}, 2020, 9 pages. \item Craig Stewart, Nikolai Vogler, Junjie Hu, {\bf Jordan Boyd-Graber}, and Graham Neubig. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_acl_interpeval.pdf}{Automatic Estimation of Simultaneous Interpreter Performance}}. \emph{Association for Computational Linguistics}, 2018, 5 pages (24\% Acceptance Rate). \item Khanh Nguyen, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_emnlp_bandit_mt.pdf}{Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback}}. \emph{Empirical Methods in Natural Language Processing}, 2017, 11 pages (26\% Acceptance Rate). \item \underline{\href{https://www.ursinus.edu/live/profiles/3125-alvin-grissom-ii}{Alvin Grissom II}}, Naho Orita, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_conll_verbpred.pdf}{Incremental Prediction of Sentence-final Verbs}}. \emph{Conference on Computational Natural Language Learning}, 2016, 10 pages (20\% Acceptance Rate). \item \underline{\href{https://hhexiy.github.io/}{He He}}, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_interpretese.pdf}{Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation}}. \emph{North American Association for Computational Linguistics}, 2016, 6 pages (29\% Acceptance Rate). \item \underline{\href{https://hhexiy.github.io/}{He He}}, \underline{\href{https://www.ursinus.edu/live/profiles/3125-alvin-grissom-ii}{Alvin Grissom II}}, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_emnlp_rewrite.pdf}{Syntax-based Rewriting for Simultaneous Machine Translation}}. \emph{Empirical Methods in Natural Language Processing}, 2015 (24\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, Vlad Eidelman, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_acl_ptlda_mt.pdf}{Polylingual Tree-Based Topic Models for Translation Domain Adaptation}}. \emph{Association for Computational Linguistics}, 2014, 11 pages (26\% Acceptance Rate). \item \underline{\href{https://www.ursinus.edu/live/profiles/3125-alvin-grissom-ii}{Alvin Grissom II}}, \underline{\href{https://hhexiy.github.io/}{He He}}, {\bf Jordan Boyd-Graber}, John Morgan, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_emnlp_simtrans.pdf}{Don't Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation}}. \emph{Empirical Methods in Natural Language Processing}, 2014, 11 pages (30\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, Vlad Edelman, and {\bf Jordan Boyd-Graber}. {\bf Topic Models for Translation Domain Adaptation}. \emph{NIPS Workshop on Topic Models: Computation, Application, and Evaluation}, 2013. \item Vladimir Eidelman, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/acl_2012_tm_for_mt.pdf}{Topic Models for Dynamic Translation Model Adaptation}}. \emph{Association for Computational Linguistics}, 2012, 5 pages (21\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Multilingual Corpora}}{}{ \begin{enumerate} \item Yoshinari Fujinuma, {\bf Jordan Boyd-Graber}, and Katharina Kann. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_acl_multilingbert.pdf}{How Does Multilingual Pretraining Affect Cross-Lingual Transferability?}}. \emph{Association for Computational Linguistics}, 2022, 9 pages (21\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, \underline{\href{http://akkikiki.github.io/about/}{Yoshinari Fujinuma}}, Michael J. Paul, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_acl_refine.pdf}{Why Overfitting Isn't Always Bad: Retrofitting Cross-Lingual Word Embeddings to Dictionaries}}. \emph{Association for Computational Linguistics}, 2020 (17.6\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, \underline{\href{http://akkikiki.github.io/about/}{Yoshinari Fujinuma}}, and {\bf Jordan Boyd-Graber}. {\bf \href{https://arxiv.org/abs/1812.09617}{Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification}}. \emph{Association for the Advancement of Artificial Intelligence}, 2020, 9 pages (20.6\% Acceptance Rate). \item \underline{\href{http://akkikiki.github.io/about/}{Yoshinari Fujinuma}}, Michael Paul, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_modularity.pdf}{A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity}}. \emph{Association for Computational Linguistics}, 2019, 10 pages (26\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, Keyulu Xu, Ken-ichi Kawarabayashi, Stefanie Jegelka, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_clwe.pdf}{Are Girls Neko or Sh{\=o}jo? {C}ross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization}}. \emph{Association for Computational Linguistics}, 2019 (18.3\% Acceptance Rate). \item Dasha Pruss, \underline{\href{http://akkikiki.github.io/about/}{Yoshinari Fujinuma}}, Ashlynn Daughton, Michael Paul, Brad Arnot, Danielle Szafir, and {\bf Jordan Boyd-Graber}. {\bf \href{https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0216922}{Zika discourse in the Americas: A multilingual topic analysis of {Twitter}}}. \emph{PlosOne}, 2019, 23 pages. \item \underline{\href{http://users.umiacs.umd.edu/~mozhi/}{Mozhi Zhang}}, \underline{\href{http://akkikiki.github.io/about/}{Yoshinari Fujinuma}}, and {\bf Jordan Boyd-Graber}. {\bf Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification}. \emph{ACL Workshop on Deep Learning Approaches for Low-Resource Natural Language Processing}, 2018, 6 pages. \item Shudong Hao, Michael J. Paul, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_naacl_mltm_eval.pdf}{Lessons from the Bible on Modern Topics: Multilingual Topic Model Evaluation on Low-Resource Languages}}. \emph{North American Association for Computational Linguistics}, 2018, 9 pages (35\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, Vlad Eidelman, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_acl_ptlda_mt.pdf}{Polylingual Tree-Based Topic Models for Translation Domain Adaptation}}. \emph{Association for Computational Linguistics}, 2014, 11 pages (26\% Acceptance Rate). \item {\bf Jordan Boyd-Graber} and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/jbg-mlslda-2010.pdf}{Holistic Sentiment Analysis Across Languages: Multilingual Supervised Latent Dirichlet Allocation}}. \emph{Empirical Methods in Natural Language Processing}, 2010, 11 pages (25\% Acceptance Rate). \item {\bf Jordan Boyd-Graber} and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/uai2009.pdf}{Multilingual Topic Models for Unaligned Text}}. \emph{Uncertainty in Artificial Intelligence}, 2009, 8 pages (31\% Acceptance Rate). \item {\bf Jordan Boyd-Graber} and David M. Blei. {\bf Multilingual Topic Models}. \emph{NIPS Workshop on Unsupervised Latent Variable Models}, 2008. \end{enumerate} } \headedsection{{\bf Question Answering}}{}{ \begin{enumerate} \item Benjamin B\"orschinger, {\bf Jordan Boyd-Graber}, Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Michelle Chen Huebscher, Wojciech Gajewski, Yannic Kilcher, Rodrigo Nogueira, and Lierni Sestorain Saralegu. {\bf \href{https://arxiv.org/abs/1911.04156}{Meta Answering for Machine Reading}}. \emph{ArXiv}, Preprint, 10 pages. \item Pedro Rodriguez, Shi Feng, Mohit Iyyer, He He, and {\bf Jordan Boyd-Graber}. {\bf \href{https://arxiv.org/abs/1904.04792}{Quizbowl: The Case for Incremental Question Answering}}. \emph{ArXiv}, Preprint, 55 pages. \item Quynh C. Nguyen, Elizabeth M. Aparicio, Michelle Jasczynski, Amara Channell Doig, Xiaohe Yue, Heran Mane, Neha Pundlik Srikanth, Francia Ximena Marin Gutierrez, Nataly Delcid, Xin He, and {\bf Jordan Boyd-Graber}. {\bf Randomized Pilot of Rosie, a Health Education Question-and-Answer Chatbot for New Mothers}. \emph{Journal of Medical Internet Research: Journal of Formative Research}, 2024. \item Srikanth, Neha Pundlik, Rupak Sarkar, Mane, Heran Y., Aparicio, Elizabeth M., Nguyen, Quynh C., Rachel Rudinger, and {\bf Jordan Boyd-Graber}. {\bf Large Language Models Help Humans Verify Truthfulness---Except When They Are Convincingly Wrong}. \emph{North American Association for Computational Linguistics}, 2024. \item \underline{\href{https://h-j-han.github.io/}{HyoJung Han}}, Marine Carpuat, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2023_emnlp_explicitation.pdf}{Automatic Explicitation to Bridge the Background Knowledge Gap in Translation and its Evaluation with Multilingual QA}}. \emph{Empirical Methods in Natural Language Processing}, 2023, 9 pages (23\% Acceptance Rate). \item Sander V Schulhoff, Jeremy Pinto, Anaum Khan, Louis-François Bouchard, \underline{\href{https://noviscl.github.io/}{Chenglei Si}}, Jordan Lee Boyd-Graber, Svetlina Anati, Valen Tagliabue, Anson Liu Kost, and Christopher R Carnahan. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2023_emnlp_hackaprompt.pdf}{Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs Through a Global Prompt Hacking Competition}}. \emph{Empirical Methods in Natural Language Processing}, 2023, 9 pages (23\% Acceptance Rate). \item \underline{\href{http://yysung.github.io/}{Yoo Yeon Sung}}, Naeemul Hassan, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2023_emnlp_videoheadline.pdf}{Not all Fake News is Written: A Dataset and Analysis of Misleading Video Headlines}}. \emph{Empirical Methods in Natural Language Processing}, 2023, 9 pages (23\% Acceptance Rate). \item Mane, Heran Y., Channell Doig, Amara, Marin Gutierrez, Francia Ximena, Jasczynski, Michelle, Yue, Xiaohe, Srikanth, Neha Pundlik, Mane, Sourabh, Sun, Abby, Moats, Rachel Ann, Patel, Pragat, He, Xin, Boyd-Graber, Jordan Lee, Aparicio, Elizabeth M., and Nguyen, Quynh C.. {\bf \href{https://journals.lww.com/jphmp/fulltext/2023/09000/practical_guidance_for_the_development_of_rosie,_a.9.aspx}{Practical Guidance for the Development of Rosie, a Health Education Question-and-Answer Chatbot for New Mothers}}. \emph{Journal of Public Health Management and Practice}, 2023. \item Shi Feng and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_emnlp_augment.pdf}{Learning to Explain Selectively: A Case Study on Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2022, 9 pages. \item \underline{\href{https://h-j-han.github.io/}{HyoJung Han}}, Marine Carpuat, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_emnlp_simqa.pdf}{SimQA: Detecting Simultaneous MT Errors through Word-by-Word Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2022, 9 pages. \item Wanrong He, \underline{Andrew Mao}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_emnlp_cheaters.pdf}{Cheater's Bowl: Human vs. Computer Search Strategies for Open-Domain QA}}. \emph{Findings of Empirical Methods in Natural Language Processing}, 2022, 9 pages. \item \underline{\href{https://noviscl.github.io/}{Chenglei Si}}, Chen Zhao, Sewon Min, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2022_emnlp_calibration.pdf}{Re-Examining Calibration: The Case of Question Answering}}. \emph{Findings of Empirical Methods in Natural Language Processing}, 2022, 9 pages. \item \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}, Joe Barrow, Alexander Hoyle, John P. Lalor, Robin Jia, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_acl_leaderboard.pdf}{Evaluation Examples Are Not Equally Informative: How Should That Change NLP Leaderboards?}}. \emph{Association for Computational Linguistics}, 2021, 9 pages (21\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, Chenyan Xiong, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_emnlp_weak_dpr.pdf}{Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation}}. \emph{Empirical Methods in Natural Language Processing}, 2021, 11 pages (26\% Acceptance Rate). \item \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_emnlp_paradigms.pdf}{Evaluation Paradigms in Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2021, 5 pages (18\% Acceptance Rate). \item Maharshi Gor, Kellie Webster, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_emnlp_qa_fairness.pdf}{Toward Deconfounding the Influence of Subject's Demographic Characteristics in Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2021, 9 pages (26\% Acceptance Rate). \item \underline{\href{https://noviscl.github.io/}{Chenglei Si}}, \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_emnlp_answer_equiv.pdf}{What's in a Name? Answer Equivalence For Open-Domain Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2021, 6 pages (18\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, Chenyan Xiong, Hal {Daum\'{e} III}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_naacl_multi_ance.pdf}{Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval}}. \emph{North American Association for Computational Linguistics}, 2021, 6 pages (23\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, Chenyan Xiong, Xin Qian, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_www_delft.pdf}{Complex Factoid Question Answering with a Free-Text Knowledge Graph}}. \emph{ACM International Conference on World Wide Web}, 2020, 11 pages (19.2\% Acceptance Rate). \item {\bf Jordan Boyd-Graber} and Benjamin B\"orschinger. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_acl_trivia.pdf}{What Question Answering can Learn from Trivia Nerds}}. \emph{Association for Computational Linguistics}, 2020 (25.4\% Acceptance Rate). \item Diggelmann, Thomas, Boyd-Graber, Jordan, Bulian, Jannis, Ciaramita, Massimiliano, and Leippold, Markus. {\bf \href{https://research.google/pubs/pub50541/}{CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims}}. \emph{NIPS Workshop on Tackling Climate Change with Machine Learning}, 2020. \item \underline{\href{http://www.ericswallace.com/}{Eric Wallace}}, \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_flipside.pdf}{Misleading Failures of Partial-input Baselines}}. \emph{Association for Computational Linguistics}, 2019, 6 pages (18\% Acceptance Rate). \item \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, Joe Barrow, \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}, Graham Neubig, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_interspeech_asr}{Mitigating Noisy Inputs for Question Answering}}. \emph{Conference of the International Speech Communication Association}, 2019, 5 pages. \item \underline{\href{http://www.cs.umd.edu/~elgohary/}{Ahmed Elgohary Ghoneim}}, \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_emnlp_sequentialqa.pdf}{Can You Unpack That? Learning to Rewrite Questions-in-Context}}. \emph{Empirical Methods in Natural Language Processing}, 2019, 6 pages. \item \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_iui_augment.pdf}{What AI can do for me: Evaluating Machine Learning Interpretations in Cooperative Play}}. \emph{Intelligent User Interfaces}, 2019 (25\% Acceptance Rate). \item \underline{\href{http://www.ericswallace.com/}{Eric Wallace}}, \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}, \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, Ikuya Yamada, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_tacl_trick.pdf}{Trick Me If You Can: Human-in-the-loop Generation of Adversarial Question Answering Examples}}. \emph{Transactions of the Association for Computational Linguistics}, 2019, 14 pages. \item \underline{\href{http://www.ericswallace.com/}{Eric Wallace}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://aclweb.org/anthology/P18-3018}{Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions}}. \emph{ACL Student Research Workshop}, 2018, 6 pages. \item \underline{\href{http://www.cs.umd.edu/~elgohary/}{Ahmed Elgohary Ghoneim}}, \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_emnlp_linked.pdf}{Dataset and Baselines for Sequential Open-Domain Question Answering}}. \emph{Empirical Methods in Natural Language Processing}, 2018, 6 pages (23\% Acceptance Rate). \item \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, \underline{\href{http://www.ericswallace.com/}{Eric Wallace}}, Alvin Grissom II, \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}, Mohit Iyyer, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_emnlp_rs.pdf}{Pathologies of Neural Models Make Interpretation Difficult}}. \emph{Empirical Methods in Natural Language Processing}, 2018, 9 pages (26\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Varun Manjunatha, Anupam Guha, Yogarshi Vyas, {\bf Jordan Boyd-Graber}, Hal {Daum\'{e} III}, and Larry Davis. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_cvpr_comics.pdf}{The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives}}. \emph{Computer Vision and Pattern Recognition}, 2017, 10 pages (30\% Acceptance Rate). \item \underline{\href{https://hhexiy.github.io/}{He He}}, {\bf Jordan Boyd-Graber}, Kevin Kwok, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_icml_opponent.pdf}{Opponent Modeling in Deep Reinforcement Learning}}. \emph{International Conference on Machine Learning}, 2016, 10 pages (24\% Acceptance Rate). \item Anupam Guha, \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_paintings.pdf}{A Distorted Skull Lies in the Bottom Center: Identifying Paintings from Text Descriptions}}. \emph{NAACL Human-Computer Question Answering Workshop}, 2016. \item Md Arafat Sultan, {\bf Jordan Boyd-Graber}, and Tamara Sumner. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_sts.pdf}{Bayesian Supervised Domain Adaptation for Short Text Similarity}}. \emph{North American Association for Computational Linguistics}, 2016, 11 pages (24\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Varun Manjunatha, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_acl_dan.pdf}{Deep Unordered Composition Rivals Syntactic Methods for Text Classification}}. \emph{Association for Computational Linguistics}, 2015, 11 pages (25\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, \underline{\href{https://hhexiy.github.io/}{He He}}, and Hal {Daum\'{e} III}. {\bf Interactive Incremental Question Answering}. \emph{Neural Information Processing Systems}, 2015. \item Anupam Guha, \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Danny Bouman, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_naacl_qb_coref.pdf}{Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers}}. \emph{North American Association for Computational Linguistics}, 2015, 11 pages (26\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, {\bf Jordan Boyd-Graber}, Leonardo Claudino, Richard Socher, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_emnlp_qb_rnn.pdf}{A Neural Network for Factoid Question Answering over Paragraphs}}. \emph{Empirical Methods in Natural Language Processing}, 2014, 12 pages (26\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, \underline{Brianna Satinoff}, \underline{\href{https://hhexiy.github.io/}{He He}}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/qb_emnlp_2012.pdf}{Besting the Quiz Master: Crowdsourcing Incremental Classification Games}}. \emph{Empirical Methods in Natural Language Processing}, 2012, 12 pages (25\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Reinforcement Learning}}{}{ \begin{enumerate} \item Wenyan Li, Alvin {Grissom II}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_findings_verbs.pdf}{An Attentive Recurrent Model for Incremental Prediction of Sentence-final Verbs}}. \emph{Findings of EMNLP}, 2020, 9 pages. \item Tianze Shi, \underline{\href{http://users.umiacs.umd.edu/~chenz/}{Chen Zhao}}, {\bf Jordan Boyd-Graber}, Hal {Daum\'{e} III}, and Lillian Lee. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_findings_qalign.pdf}{On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries}}. \emph{Findings of EMNLP}, 2020, 9 pages. \item Khanh Nguyen, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_emnlp_bandit_mt.pdf}{Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback}}. \emph{Empirical Methods in Natural Language Processing}, 2017, 11 pages (26\% Acceptance Rate). \item \underline{\href{https://hhexiy.github.io/}{He He}}, {\bf Jordan Boyd-Graber}, Kevin Kwok, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_icml_opponent.pdf}{Opponent Modeling in Deep Reinforcement Learning}}. \emph{International Conference on Machine Learning}, 2016, 10 pages (24\% Acceptance Rate). \item \underline{\href{https://www.ursinus.edu/live/profiles/3125-alvin-grissom-ii}{Alvin Grissom II}}, \underline{\href{https://hhexiy.github.io/}{He He}}, {\bf Jordan Boyd-Graber}, John Morgan, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_emnlp_simtrans.pdf}{Don't Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation}}. \emph{Empirical Methods in Natural Language Processing}, 2014, 11 pages (30\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, \underline{Brianna Satinoff}, \underline{\href{https://hhexiy.github.io/}{He He}}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/qb_emnlp_2012.pdf}{Besting the Quiz Master: Crowdsourcing Incremental Classification Games}}. \emph{Empirical Methods in Natural Language Processing}, 2012, 12 pages (25\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Sentiment and Perspective}}{}{ \begin{enumerate} \item \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, Benny Cheng, \underline{\href{http://www.cs.umd.edu/~elgohary/}{Ahmed Elgohary Ghoneim}}, Joe Barrow, Cristian Danescu-Niculescu-Mizil, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_acl_diplomacy.pdf}{It Takes Two to Lie: One to Lie and One to Listen}}. \emph{Association for Computational Linguistics}, 2020 (25.4\% Acceptance Rate). \item Francesco Saverio Varini, {\bf Jordan Boyd-Graber}, Massimiliano Ciaramita, and Markus Leippold. {\bf ClimaText: A Dataset for Climate Change Topic Detection}. \emph{NeurIPS Workshop on Tackling Climate Change with Machine Learning}, 2020. \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Varun Manjunatha, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_acl_dan.pdf}{Deep Unordered Composition Rivals Syntactic Methods for Text Classification}}. \emph{Association for Computational Linguistics}, 2015, 11 pages (25\% Acceptance Rate). \item Vlad Niculae, Srijan Kumar, {\bf Jordan Boyd-Graber}, and Cristian Danescu-Niculescu-Mizil. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_acl_diplomacy.pdf}{Linguistic Harbingers of Betrayal: A Case Study on an Online Strategy Game}}. \emph{Association for Computational Linguistics}, 2015, 10 pages (25\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Philip Resnik, and Kristina Miler. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_acl_teaparty.pdf}{Tea Party in the House: A Hierarchical Ideal Point Topic Model and Its Application to Republican Legislators in the 112th Congress}}. \emph{Association for Computational Linguistics}, 2015, 11 pages (25\% Acceptance Rate). \item Stephen H. Bach, Bert Huang, {\bf Jordan Boyd-Graber}, and Lise Getoor. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_icml_paired_dual.pdf}{Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs}}. \emph{International Conference on Machine Learning}, 2015, 10 pages (20\% Acceptance Rate). \item Philip Resnik, William Armstrong, Leonardo Claudino, \underline{\href{http://www.umiacs.umd.edu/~daithang/}{Thang Nguyen}}, \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, and {\bf Jordan Boyd-Graber}. {\bf Beyond {LDA}: Exploring Supervised Topic Modeling for Depression-Related Language in Twitter}. \emph{NAACL Workshop on Cognitive Modeling and Computational Linguistics}, 2015. \item \underline{\href{http://www.umiacs.umd.edu/~daithang/}{Thang Nguyen}}, {\bf Jordan Boyd-Graber}, Jeff Lund, Kevin Seppi, and Eric Ringger. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_naacl_supervised_anchor.pdf}{Is your anchor going up or down? {F}ast and accurate supervised topic models}}. \emph{North American Association for Computational Linguistics}, 2015, 10 pages (26\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Peter Enns, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_acl_rnn_ideology.pdf}{Political Ideology Detection Using Recursive Neural Networks}}. \emph{Association for Computational Linguistics}, 2014, 10 pages (26\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_emnlp_howto_gibbs.pdf}{Sometimes Average is Best: The Importance of Averaging for Prediction using MCMC Inference in Topic Modeling}}. \emph{Empirical Methods in Natural Language Processing}, 2014, 6 pages (30\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Philip Resnik, Deborah Cai, Jennifer Midberry, and Yuanxin Wang. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_mlj_influencer.pdf}{Modeling Topic Control to Detect Influence in Conversations using Nonparametric Topic Models}}. \emph{Machine Learning}, 2014, 48 pages. \item \underline{Kimberly Glasgow}, Clay Fink, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_icwsm_grief.pdf}{Our grief is unspeakable: Measuring the community impact of a tragedy}}. \emph{The International AAAI Conference on Weblogs and Social Media}, 2014, 9 pages (20\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, \underline{Kimberly Glasgow}, and Jackie Sauter Zajac. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_spoiler.pdf}{Spoiler Alert: Machine Learning Approaches to Detect Social Media Posts with Revelatory Information}}. \emph{ASIST 2013: The 76th Annual Meeting of the American Society for Information Science and Technology}, 2013, 9 pages. \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_shlda.pdf}{Lexical and Hierarchical Topic Regression}}. \emph{Neural Information Processing Systems}, 2013, 10 pages (25\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_argviz.pdf}{Argviz: Interactive Visualization of Topic Dynamics in Multi-party Conversations}}. \emph{North American Association for Computational Linguistics}, 2013, 4 pages (50\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/acl_2012_sits.pdf}{{SITS}: A Hierarchical Nonparametric Model using Speaker Identity for Topic Segmentation in Multiparty Conversations}}. \emph{Association for Computational Linguistics}, 2012, 10 pages (19\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf ``I Want to Talk About, Again, My Record On Energy~\dots'': Modeling Topic Control in Conversations using Speaker-centric Nonparametric Topic Models}. \emph{Mid-Atlantic Student Colloquium on Speech, Language, and Learning}, 2012. \item Asad B. Sayeed, {\bf Jordan Boyd-Graber}, Bryan Rusk, and Amy Weinberg. {\bf \href{http://umiacs.umd.edu/~jbg//docs/srt_naacl_2012.pdf}{Grammatical structures for word-level sentiment detection}}. \emph{North American Association for Computational Linguistics}, 2012, 10 pages (31\% Acceptance Rate). \item Clay Templeton, Travis Brown, Sayan Battacharyya, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/slda_civil_war.pdf}{Mining the Dispatch under Supervision: Using Casualty Counts to Guide Topics from the Richmond Daily Dispatch Corpus}}. \emph{Chicago Colloquium on Digital Humanities and Computer Science}, 2011, 7 pages. \item Clay Templeton, Kenneth R. Fleischmann, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/simulating_audiences.pdf}{Simulating Audiences: Automating Analysis of Values, Attitudes, and Sentiment}}. \emph{IEEE International Conference on Social Computing}, 2011, 4 pages (10\% Acceptance Rate). \item Pranav Anand, Joseph King, {\bf Jordan Boyd-Graber}, Earl Wagner, Craig Martell, Douglas W. Oard, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/persuasion.pdf}{Believe Me: We Can Do This!}}. \emph{The AAAI 2011 workshop on Computational Models of Natural Argument}, 2011, 5 pages. \item Clay Templeton, Kenneth R. Fleischmann, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/iconference-2011-comparing.pdf}{Comparing Values and Sentiment Using Mechanical Turk}}. \emph{iConference}, 2011, 2 pages. \item Kenneth R. Fleischmann, Clay Templeton, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/iconference-2011-learning.pdf}{Modeling Diverse Standpoints in Text Classification: Learning to Be Human by Modeling Human Values}}. \emph{iConference}, 2011, 2 pages. \item {\bf Jordan Boyd-Graber} and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/jbg-mlslda-2010.pdf}{Holistic Sentiment Analysis Across Languages: Multilingual Supervised Latent Dirichlet Allocation}}. \emph{Empirical Methods in Natural Language Processing}, 2010, 11 pages (25\% Acceptance Rate). \item \underline{Eric Hardisty}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/adapted_naive_bayes.pdf}{Modeling Perspective using Adaptor Grammars}}. \emph{Empirical Methods in Natural Language Processing}, 2010, 10 pages (25\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Spectral Methods}}{}{ \begin{enumerate} \item Jeffrey Lund, Piper Armstrong, Wilson Fearn, Stephen Cowley, Courtni Byun, {\bf Jordan Boyd-Graber}, and Kevin Seppi. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_local.pdf}{Automatic and Human Evaluation of Local Topic Quality}}. \emph{Association for Computational Linguistics}, 2019, 10 pages (26\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, Benjamin {Van Durme}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_neurips_mtanchor.pdf}{Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages}}. \emph{Neural Information Processing Systems}, 2018, 10 pages (21\% Acceptance Rate). \item Jeff Lund, Connor Cook, Kevin Seppi, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_acl_multiword_anchors.pdf}{Tandem Anchoring: A Multiword Anchor Approach for Interactive Topic Modeling}}. \emph{Association for Computational Linguistics}, 2017, 10 pages (22\% Acceptance Rate). \item \underline{\href{http://www.umiacs.umd.edu/~daithang/}{Thang Nguyen}}, {\bf Jordan Boyd-Graber}, Jeff Lund, Kevin Seppi, and Eric Ringger. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_naacl_supervised_anchor.pdf}{Is your anchor going up or down? {F}ast and accurate supervised topic models}}. \emph{North American Association for Computational Linguistics}, 2015, 10 pages (26\% Acceptance Rate). \item \underline{\href{http://www.umiacs.umd.edu/~daithang/}{Thang Nguyen}}, \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_acl_anchor_reg.pdf}{Anchors Regularized: Adding Robustness and Extensibility to Scalable Topic-Modeling Algorithms}}. \emph{Association for Computational Linguistics}, 2014, 10 pages (26\% Acceptance Rate). \item Thang Nguyen, \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, and {\bf Jordan Boyd-Graber}. {\bf Evaluating Regularized Anchor Words}. \emph{NIPS Workshop on Topic Models: Computation, Application, and Evaluation}, 2013. \end{enumerate} } \headedsection{{\bf Speech}}{}{ \begin{enumerate} \item \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, Joe Barrow, \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}, Graham Neubig, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_interspeech_asr}{Mitigating Noisy Inputs for Question Answering}}. \emph{Conference of the International Speech Communication Association}, 2019, 5 pages. \end{enumerate} } \headedsection{{\bf Syntax}}{}{ \begin{enumerate} \item \underline{\href{https://hhexiy.github.io/}{He He}}, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_naacl_interpretese.pdf}{Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation}}. \emph{North American Association for Computational Linguistics}, 2016, 6 pages (29\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Varun Manjunatha, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_acl_dan.pdf}{Deep Unordered Composition Rivals Syntactic Methods for Text Classification}}. \emph{Association for Computational Linguistics}, 2015, 11 pages (25\% Acceptance Rate). \item Anupam Guha, \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Danny Bouman, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_naacl_qb_coref.pdf}{Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers}}. \emph{North American Association for Computational Linguistics}, 2015, 11 pages (26\% Acceptance Rate). \item Naho Orita, Naomi Feldman, and {\bf Jordan Boyd-Graber}. {\bf Quantifying the role of discourse topicality in speakers' choices of referring expressions}. \emph{ACL Workshop on Cognitive Modeling and Computational Linguistics}, 2014. \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, Peter Enns, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_acl_rnn_ideology.pdf}{Political Ideology Detection Using Recursive Neural Networks}}. \emph{Association for Computational Linguistics}, 2014, 10 pages (26\% Acceptance Rate). \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, {\bf Jordan Boyd-Graber}, Leonardo Claudino, Richard Socher, and Hal {Daum\'{e} III}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_emnlp_qb_rnn.pdf}{A Neural Network for Factoid Question Answering over Paragraphs}}. \emph{Empirical Methods in Natural Language Processing}, 2014, 12 pages (26\% Acceptance Rate). \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, {\bf Jordan Boyd-Graber}, and Shay B. Cohen. {\bf Hybrid Online Inference with Adaptor Grammars}. \emph{NIPS Workshop on Advances in Variational Inference}, 2014. \item \underline{\href{https://people.cs.umass.edu/~miyyer/}{Mohit Iyyer}}, {\bf Jordan Boyd-Graber}, and Hal {Daum\'{e} III}. {\bf Generating Sentences from Semantic Vector Space Representations}. \emph{NIPS Workshop on Learning Semantics}, 2014. \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, {\bf Jordan Boyd-Graber}, and Shay B. Cohen. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_tacl_ag_vb_online.pdf}{Online Adaptor Grammars with Hybrid Inference}}. \emph{Transactions of the Association for Computational Linguistics}, 2014, 12 pages. \item Naho Orita, Rebecca McKeown, Naomi H. Feldman, Jeffrey Lidz, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_cogsci_pronoun.pdf}{Discovering Pronoun Categories using Discourse Information}}. \emph{Proceedings of the Cognitive Science Society}, 2013, 6 pages. \item Asad B. Sayeed, {\bf Jordan Boyd-Graber}, Bryan Rusk, and Amy Weinberg. {\bf \href{http://umiacs.umd.edu/~jbg//docs/srt_naacl_2012.pdf}{Grammatical structures for word-level sentiment detection}}. \emph{North American Association for Computational Linguistics}, 2012, 10 pages (31\% Acceptance Rate). \item {\bf Jordan Boyd-Graber} and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/nips2008.pdf}{Syntactic Topic Models}}. \emph{Neural Information Processing Systems}, 2008, 8 pages (25\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Topic Models}}{}{ \begin{enumerate} \item Zongxia Li, Andrew Mao, Daniel Kofi Stephens, Pranav Goel, Emily Walpole, Juan Francisco Fung, Alden Dima, and Jordan Lee Boyd-Graber. {\bf TENOR: Topic Enabled Neural Organization and Recommendation: Evaluating Topic Models in Task Based Settings}. \emph{European Association for Computational Linguistics}, 2024 (21\% Acceptance Rate). \item Alexander Hoyle, Pranav Goel, \underline{\href{http://denispeskov.github.io/}{Denis Peskov}}, Andrew Hian-Cheong, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_neurips_incoherence.pdf}{Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence}}. \emph{Neural Information Processing Systems}, 2021, 10 pages (26\% Acceptance Rate). \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Varun Kumar, {\bf Jordan Boyd-Graber}, Kevin Seppi, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_iui_control.pdf}{Digging into User Control: Perceptions of Adherence and Instability in Transparent Models}}. \emph{Intelligent User Interfaces}, 2020, 12 pages (23\% Acceptance Rate). \item \underline{\href{https://csel.cs.colorado.edu/~fegu1724/}{Fenfei Guo}}, {\bf Jordan Boyd-Graber}, Mohit Iyyer, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2020_lrec_sense.pdf}{Which Evaluations Uncover Sense Representations that Actually Make Sense?}}. \emph{Linguistic Resources and Evaluation Conference}, 2020, 10 pages. \item Francesco Saverio Varini, {\bf Jordan Boyd-Graber}, Massimiliano Ciaramita, and Markus Leippold. {\bf ClimaText: A Dataset for Climate Change Topic Detection}. \emph{NeurIPS Workshop on Tackling Climate Change with Machine Learning}, 2020. \item Jeffrey Lund, Piper Armstrong, Wilson Fearn, Stephen Cowley, Courtni Byun, {\bf Jordan Boyd-Graber}, and Kevin Seppi. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_local.pdf}{Automatic and Human Evaluation of Local Topic Quality}}. \emph{Association for Computational Linguistics}, 2019, 10 pages (26\% Acceptance Rate). \item Varun Kumar, \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Leah Findlater, Kevin Seppi, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_control.pdf}{Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models}}. \emph{Association for Computational Linguistics}, 2019, 6 pages (18\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_emnlp_mtm.pdf}{A Multilingual Topic Model for Learning Weighted Topic Links Across Incomparable Corpora}}. \emph{Empirical Methods in Natural Language Processing}, 2019, 6 pages. \item Dasha Pruss, \underline{\href{http://akkikiki.github.io/about/}{Yoshinari Fujinuma}}, Ashlynn Daughton, Michael Paul, Brad Arnot, Danielle Szafir, and {\bf Jordan Boyd-Graber}. {\bf \href{https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0216922}{Zika discourse in the Americas: A multilingual topic analysis of {Twitter}}}. \emph{PlosOne}, 2019, 23 pages. \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Varun Kumar, {\bf Jordan Boyd-Graber}, Kevin Seppi, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_iui_itm.pdf}{User-Centered Design and Evaluation of a Human-in-the-Loop Topic Modeling System}}. \emph{Intelligent User Interfaces}, 2018, 12 pages (23\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~myuan/}{Michelle Yuan}}, Benjamin {Van Durme}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_neurips_mtanchor.pdf}{Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages}}. \emph{Neural Information Processing Systems}, 2018, 10 pages (21\% Acceptance Rate). \item Shudong Hao, Michael J. Paul, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_naacl_mltm_eval.pdf}{Lessons from the Bible on Modern Topics: Multilingual Topic Model Evaluation on Low-Resource Languages}}. \emph{North American Association for Computational Linguistics}, 2018, 9 pages (35\% Acceptance Rate). \item Aaron Gerow, Yuening Hu, {\bf Jordan Boyd-Graber}, David M. Blei, and James A. Evans. {\bf Measuring Discursive Influence Across Scholarship}. \emph{Proceedings of the National Academies of Science}, 2018. \item {\bf Jordan Boyd-Graber}, Yuening Hu, and David Mimno. {\bf \href{http://www.nowpublishers.com/article/Details/INR-030}{Applications of Topic Models}}. 2017, 153 pages. \item Jeff Lund, Connor Cook, Kevin Seppi, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_acl_multiword_anchors.pdf}{Tandem Anchoring: A Multiword Anchor Approach for Interactive Topic Modeling}}. \emph{Association for Computational Linguistics}, 2017, 10 pages (22\% Acceptance Rate). \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Varun Kumar, {\bf Jordan Boyd-Graber}, Kevin Seppi, and Leah Findlater. {\bf \href{http://visualization.ischool.uw.edu/hci_uncertainty/papers/Paper11.pdf}{Accounting for Input Uncertainty in Human-in-the-Loop Systems}}. \emph{CHI 2017 Designing for Uncertainty Workshop}, 2017. \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_emnlp_tree_prior.pdf}{Adapting Topic Models using Lexical Associations with Tree Priors}}. \emph{Empirical Methods in Natural Language Processing}, 2017, 6 pages (18\% Acceptance Rate). \item You Lu, Jeff Lund, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_emnlp_adagrad_olda.pdf}{Why ADAGRAD Fails for Online Topic Modeling}}. \emph{Empirical Methods in Natural Language Processing}, 2017, 6 pages (18\% Acceptance Rate). \item Tak Yeon Lee, \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Kevin Seppi, Niklas Elmqvist, {\bf Jordan Boyd-Graber}, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_ijhcs_human_touch.pdf}{The Human Touch: How Non-expert Users Perceive, Interpret, and Fix Topic Models}}. \emph{International Journal of Human-Computer Studies}, 2017, 27 pages. \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Tak Yeon Lee, \underline{\href{https://www.microsoft.com/en-us/research/people/fopoursa/}{Forough Poursabzi-Sangdeh}}, {\bf Jordan Boyd-Graber}, Kevin Seppi, Niklas Elmqvist, and Leah Findlater. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_tacl_eval_tm_viz.pdf}{Evaluating Visual Representations for Topic Understanding and Their Effects on Manually Generated Labels}}. \emph{Transactions of the Association for Computational Linguistics}, 2017, 15 pages. \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_acl_docblock.pdf}{A Discriminative Topic Model using Document Network Structure}}. \emph{Association for Computational Linguistics}, 2016, 10 pages (28\% Acceptance Rate). \item \underline{\href{https://www.microsoft.com/en-us/research/people/fopoursa/}{Forough Poursabzi-Sangdeh}}, {\bf Jordan Boyd-Graber}, Leah Findlater, and Kevin Seppi. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2016_acl_doclabel.pdf}{ALTO: Active Learning with Topic Overviews for Speeding Label Induction and Document Labeling}}. \emph{Association for Computational Linguistics}, 2016 (28\% Acceptance Rate). \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Tak Yeon Lee, \underline{\href{https://www.microsoft.com/en-us/research/people/fopoursa/}{Forough Poursabzi-Sangdeh}}, {\bf Jordan Boyd-Graber}, Kevin Seppi, Niklas Elmqvist, and Leah Findlater. {\bf Human-Centered and Interactive: Expanding the Impact of Topic Models}. \emph{CHI Human Centred Machine Learning Workshop}, 2016. \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf Birds of a Feather in the Same Nest: A Discriminative Topic Model using Block-based Priors}. \emph{Mid-Atlantic Student Colloquium on Speech, Language, and Learning}, 2016. \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Philip Resnik, and Kristina Miler. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_acl_teaparty.pdf}{Tea Party in the House: A Hierarchical Ideal Point Topic Model and Its Application to Republican Legislators in the 112th Congress}}. \emph{Association for Computational Linguistics}, 2015, 11 pages (25\% Acceptance Rate). \item Paul Felt, Eric Ringger, {\bf Jordan Boyd-Graber}, and Kevin Seppi. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_conll_cslda.pdf}{Making the Most of Crowdsourced Document Annotations: Confused Supervised {LDA}}}. \emph{Conference on Computational Natural Language Learning}, 2015, 10 pages (30\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~wwyang/}{Weiwei Yang}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_emnlp_hinge_link.pdf}{Birds of a Feather Linked Together: A Discriminative Topic Model using Link-based Priors}}. \emph{Empirical Methods in Natural Language Processing}, 2015, 5 pages (28\% Acceptance Rate). \item Yi Yang, Doug Downey, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_emnlp_fast_priors.pdf}{Efficient Methods for Incorporating Knowledge into Topic Models}}. \emph{Empirical Methods in Natural Language Processing}, 2015, 9 pages (24\% Acceptance Rate). \item \underline{\href{https://www.microsoft.com/en-us/research/people/fopoursa/}{Forough Poursabzi-Sangdeh}} and {\bf Jordan Boyd-Graber}. {\bf Speeding Document Annotation with Topic Models}. \emph{NAACL Student Research Workshop}, 2015. \item Philip Resnik, William Armstrong, Leonardo Claudino, \underline{\href{http://www.umiacs.umd.edu/~daithang/}{Thang Nguyen}}, \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, and {\bf Jordan Boyd-Graber}. {\bf Beyond {LDA}: Exploring Supervised Topic Modeling for Depression-Related Language in Twitter}. \emph{NAACL Workshop on Cognitive Modeling and Computational Linguistics}, 2015. \item \underline{\href{http://www.umiacs.umd.edu/~daithang/}{Thang Nguyen}}, {\bf Jordan Boyd-Graber}, Jeff Lund, Kevin Seppi, and Eric Ringger. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_naacl_supervised_anchor.pdf}{Is your anchor going up or down? {F}ast and accurate supervised topic models}}. \emph{North American Association for Computational Linguistics}, 2015, 10 pages (26\% Acceptance Rate). \item Naho Orita, Naomi Feldman, and {\bf Jordan Boyd-Graber}. {\bf Quantifying the role of discourse topicality in speakers' choices of referring expressions}. \emph{ACL Workshop on Cognitive Modeling and Computational Linguistics}, 2014. \item \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Jason Chuang, \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, and Leah Findlater. {\bf Concurrent Visualization of Relationships between Words and Topics in Topic Models}. \emph{ACL Workshop on Workshop on Interactive Language Learning, Visualization, and Interfaces}, 2014. \item \underline{\href{http://www.umiacs.umd.edu/~daithang/}{Thang Nguyen}}, \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_acl_anchor_reg.pdf}{Anchors Regularized: Adding Robustness and Extensibility to Scalable Topic-Modeling Algorithms}}. \emph{Association for Computational Linguistics}, 2014, 10 pages (26\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, Vlad Eidelman, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_acl_ptlda_mt.pdf}{Polylingual Tree-Based Topic Models for Translation Domain Adaptation}}. \emph{Association for Computational Linguistics}, 2014, 11 pages (26\% Acceptance Rate). \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_emnlp_howto_gibbs.pdf}{Sometimes Average is Best: The Importance of Averaging for Prediction using MCMC Inference in Topic Modeling}}. \emph{Empirical Methods in Natural Language Processing}, 2014, 6 pages (30\% Acceptance Rate). \item {\bf Jordan Boyd-Graber}, David Mimno, and David Newman. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_book_chapter_care_and_feeding.pdf}{Care and Feeding of Topic Models: Problems, Diagnostics, and Improvements}}. \emph{Handbook of Mixed Membership Models and Their Applications}, 2014, 39 pages. \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, Brianna Satinoff, and \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_mlj_itm.pdf}{Interactive Topic Modeling}}. \emph{Machine Learning}, 2014, 56 pages. \item Jason Chuang, John D. Wilkerson, Rebecca Weiss, Dustin Tingley, Brandon M. Stewart, Margaret E. Roberts, \underline{\href{https://www.microsoft.com/en-us/research/people/fopoursa/}{Forough Poursabzi-Sangdeh}}, Justin Grimmer, Leah Findlater, {\bf Jordan Boyd-Graber}, and Jeffrey Heer. {\bf Computer-Assisted Content Analysis: Topic Models for Exploring Multiple Subjective Interpretations}. \emph{NIPS Workshop on Human-Propelled Machine Learning}, 2014. \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Philip Resnik, and Jonathan Chang. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_nips_l2h.pdf}{Learning a Concept Hierarchy from Multi-labeled Documents}}. \emph{Neural Information Processing Systems}, 2014, 9 pages (25\% Acceptance Rate). \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_icml_infvoc.pdf}{Online Topic Models with Infinite Vocabulary}}. \emph{International Conference on Machine Learning}, 2013, 9 pages (20\% Acceptance Rate). \item Thang Nguyen, \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, and {\bf Jordan Boyd-Graber}. {\bf Evaluating Regularized Anchor Words}. \emph{NIPS Workshop on Topic Models: Computation, Application, and Evaluation}, 2013. \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, Vlad Edelman, and {\bf Jordan Boyd-Graber}. {\bf Topic Models for Translation Domain Adaptation}. \emph{NIPS Workshop on Topic Models: Computation, Application, and Evaluation}, 2013. \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, Jonathan Chang, and Philip Resnik. {\bf Tree-Based Label Dependency Topic Models}. \emph{NIPS Workshop on Topic Models: Computation, Application, and Evaluation}, 2013. \item \underline{\href{http://www.cs.umd.edu/~vietan/index.htm}{Viet-An Nguyen}}, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_shlda.pdf}{Lexical and Hierarchical Topic Regression}}. \emph{Neural Information Processing Systems}, 2013, 10 pages (25\% Acceptance Rate). \item Naho Orita, Rebecca McKeown, Naomi H. Feldman, Jeffrey Lidz, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_cogsci_pronoun.pdf}{Discovering Pronoun Categories using Discourse Information}}. \emph{Proceedings of the Cognitive Science Society}, 2013, 6 pages. \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, {\bf Jordan Boyd-Graber}, Nima Asadi, and \underline{Mohamad (Jude) Alkhouja}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2012_www_mrlda.pdf}{{Mr. LDA}: A Flexible Large Scale Topic Modeling Package using Variational Inference in MapReduce}}. \emph{ACM International Conference on World Wide Web}, 2012, 10 pages (12\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/acl_2012_fttm.pdf}{Efficient Tree-Based Topic Modeling}}. \emph{Association for Computational Linguistics}, 2012, 5 pages (21\% Acceptance Rate). \item Vladimir Eidelman, {\bf Jordan Boyd-Graber}, and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/acl_2012_tm_for_mt.pdf}{Topic Models for Dynamic Translation Model Adaptation}}. \emph{Association for Computational Linguistics}, 2012, 5 pages (21\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}} and {\bf Jordan Boyd-Graber}. {\bf Suggesting Constraints for Interactive Topic Modeling}. \emph{ICML Workshop on Machine Learning in Human Computation and Crowdsourcing}, 2012. \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}} and {\bf Jordan Boyd-Graber}. {\bf Online Topic Model with Infinite Vocabulary}. \emph{Mid-Atlantic Student Colloquium on Speech, Language, and Learning}, 2012. \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, {\bf Jordan Boyd-Graber}, and \underline{Brianna Satinoff}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/itm.pdf}{Interactive Topic Modeling}}. \emph{Association for Computational Linguistics}, 2011, 10 pages (25\% Acceptance Rate). \item Clay Templeton, Travis Brown, Sayan Battacharyya, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/slda_civil_war.pdf}{Mining the Dispatch under Supervision: Using Casualty Counts to Guide Topics from the Richmond Daily Dispatch Corpus}}. \emph{Chicago Colloquium on Digital Humanities and Computer Science}, 2011, 7 pages. \item {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2010_jbg_thesis.pdf}{Linguistic Extensions of Topic Models}}. 2010, 142 pages. \item {\bf Jordan Boyd-Graber} and Philip Resnik. {\bf \href{http://umiacs.umd.edu/~jbg//docs/jbg-mlslda-2010.pdf}{Holistic Sentiment Analysis Across Languages: Multilingual Supervised Latent Dirichlet Allocation}}. \emph{Empirical Methods in Natural Language Processing}, 2010, 11 pages (25\% Acceptance Rate). \item Jonathan Chang, {\bf Jordan Boyd-Graber}, and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/kdd2009.pdf}{Connections between the Lines: Augmenting Social Networks with Text}}. \emph{Knowledge Discovery and Data Mining}, 2009, 9 pages (9\% Acceptance Rate). \item Jonathan Chang, {\bf Jordan Boyd-Graber}, Chong Wang, Sean Gerrish, and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/nips2009-rtl.pdf}{Reading Tea Leaves: How Humans Interpret Topic Models}}. \emph{Neural Information Processing Systems}, 2009, 9 pages (24\% Acceptance Rate). \item {\bf Jordan Boyd-Graber} and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/uai2009.pdf}{Multilingual Topic Models for Unaligned Text}}. \emph{Uncertainty in Artificial Intelligence}, 2009, 8 pages (31\% Acceptance Rate). \item Jonathan Chang, {\bf Jordan Boyd-Graber}, and David M. Blei. {\bf Discovering social networks from free text}. \emph{3rd Annual Machine Learning Symposium}, 2008. \item {\bf Jordan Boyd-Graber} and David M. Blei. {\bf Multilingual Topic Models}. \emph{NIPS Workshop on Unsupervised Latent Variable Models}, 2008. \item {\bf Jordan Boyd-Graber} and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/nips2008.pdf}{Syntactic Topic Models}}. \emph{Neural Information Processing Systems}, 2008, 8 pages (25\% Acceptance Rate). \item {\bf Jordan Boyd-Graber} and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/jbg-SEMEVAL07.pdf}{{PUTOP}: {T}urning Predominant Senses into a Topic Model for {WSD}}}. \emph{4th International Workshop on Semantic Evaluations}, 2007, 5 pages. \item {\bf Jordan Boyd-Graber}, David M. Blei, and Xiaojin Zhu. {\bf \href{http://umiacs.umd.edu/~jbg//docs/jbg-EMNLP07.pdf}{A Topic Model for Word Sense Disambiguation}}. \emph{Empirical Methods in Natural Language Processing}, 2007, 10 pages (27\% Acceptance Rate). \end{enumerate} } \headedsection{{\bf Variational Inference}}{}{ \begin{enumerate} \item \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}, Joe Barrow, Alexander Hoyle, John P. Lalor, Robin Jia, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2021_acl_leaderboard.pdf}{Evaluation Examples Are Not Equally Informative: How Should That Change NLP Leaderboards?}}. \emph{Association for Computational Linguistics}, 2021, 9 pages (21\% Acceptance Rate). \item Varun Kumar, \underline{\href{http://alisonmsmith.github.io/}{Alison Smith}}, Leah Findlater, Kevin Seppi, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2019_acl_control.pdf}{Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models}}. \emph{Association for Computational Linguistics}, 2019, 6 pages (18\% Acceptance Rate). \item Paul Felt, Eric Ringger, Kevin Seppi, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_coling_measurements.pdf}{Learning from Measurements in Crowdsourcing Models: Inferring Ground Truth from Diverse Annotation Types}}. \emph{International Conference on Computational Linguistics}, 2018, 10 pages (37\% Acceptance Rate). \item Aaron Gerow, Yuening Hu, {\bf Jordan Boyd-Graber}, David M. Blei, and James A. Evans. {\bf Measuring Discursive Influence Across Scholarship}. \emph{Proceedings of the National Academies of Science}, 2018. \item You Lu, Jeff Lund, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2017_emnlp_adagrad_olda.pdf}{Why ADAGRAD Fails for Online Topic Modeling}}. \emph{Empirical Methods in Natural Language Processing}, 2017, 6 pages (18\% Acceptance Rate). \item Stephen H. Bach, Bert Huang, {\bf Jordan Boyd-Graber}, and Lise Getoor. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2015_icml_paired_dual.pdf}{Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs}}. \emph{International Conference on Machine Learning}, 2015, 10 pages (20\% Acceptance Rate). \item \underline{\href{https://scholar.google.com/citations?user=mO_62fQAAAAJ&hl=en}{Yuening Hu}}, \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, Vlad Eidelman, and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_acl_ptlda_mt.pdf}{Polylingual Tree-Based Topic Models for Translation Domain Adaptation}}. \emph{Association for Computational Linguistics}, 2014, 11 pages (26\% Acceptance Rate). \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, {\bf Jordan Boyd-Graber}, and Shay B. Cohen. {\bf Hybrid Online Inference with Adaptor Grammars}. \emph{NIPS Workshop on Advances in Variational Inference}, 2014. \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}}, {\bf Jordan Boyd-Graber}, and Shay B. Cohen. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2014_tacl_ag_vb_online.pdf}{Online Adaptor Grammars with Hybrid Inference}}. \emph{Transactions of the Association for Computational Linguistics}, 2014, 12 pages. \item \underline{\href{https://kzhai.github.io/}{Ke Zhai}} and {\bf Jordan Boyd-Graber}. {\bf \href{http://umiacs.umd.edu/~jbg//docs/2013_icml_infvoc.pdf}{Online Topic Models with Infinite Vocabulary}}. \emph{International Conference on Machine Learning}, 2013, 9 pages (20\% Acceptance Rate). \item Jonathan Chang, {\bf Jordan Boyd-Graber}, and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/kdd2009.pdf}{Connections between the Lines: Augmenting Social Networks with Text}}. \emph{Knowledge Discovery and Data Mining}, 2009, 9 pages (9\% Acceptance Rate). \item {\bf Jordan Boyd-Graber} and David M. Blei. {\bf \href{http://umiacs.umd.edu/~jbg//docs/nips2008.pdf}{Syntactic Topic Models}}. \emph{Neural Information Processing Systems}, 2008, 8 pages (25\% Acceptance Rate). \end{enumerate} }