\vspace{.1cm}
Students directly advised or co-advised \underline{in underline}.
\vspace{.4cm}
\headedsection{{\bf ASED}}{}{


\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).


\end{enumerate}
}
\headedsection{{\bf Adaptive Heads-up Displays for Simultaneous Interpretation}}{}{


\begin{enumerate}
	 \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 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 \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 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).


\end{enumerate}
}
\headedsection{{\bf Adobe}}{}{


\begin{enumerate}
	 \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 \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).


\end{enumerate}
}
\headedsection{{\bf BETTER}}{}{


\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 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{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://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).


\end{enumerate}
}
\headedsection{{\bf CAREER}}{}{


\begin{enumerate}
	 \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 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{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 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://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 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 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://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://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 {\bf Jordan Boyd-Graber}, \underline{\href{http://users.umiacs.umd.edu/~shifeng/}{Shi Feng}}, and \underline{\href{https://www.pedro.ai/}{Pedro Rodriguez}}.  {\bf \href{http://umiacs.umd.edu/~jbg//docs/2018_nips_qbcomp.pdf}{Human-Computer Question Answering: The Case for Quizbowl}}.  \emph{The NIPS '17 Competition: Building Intelligent Systems}, 2018, 10 pages.


\end{enumerate}
}
\headedsection{{\bf Closing the Loop}}{}{


\begin{enumerate}
	 \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 \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 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 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://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://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 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 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 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 {\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 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 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 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{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://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 \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).


\end{enumerate}
}
\headedsection{{\bf Cross-Language Bayesian Models for Web-Scale Text Analysis}}{}{


\begin{enumerate}
	 \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://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://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 \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{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 {\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{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{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{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).


\end{enumerate}
}
\headedsection{{\bf DADC}}{}{


\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{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.


\end{enumerate}
}
\headedsection{{\bf DADC}}{}{


\begin{enumerate}
	 \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).


\end{enumerate}
}
\headedsection{{\bf FACT}}{}{


\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.


\end{enumerate}
}
\headedsection{{\bf LORELEI}}{}{


\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.


\end{enumerate}
}
\headedsection{{\bf LORELEI}}{}{


\begin{enumerate}
	 \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 \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://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 \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 \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{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).


\end{enumerate}
}
\headedsection{{\bf NIST}}{}{


\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).


\end{enumerate}
}
\headedsection{{\bf Rosie}}{}{


\begin{enumerate}
	 \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.


\end{enumerate}
}
\headedsection{{\bf Rosie}}{}{


\begin{enumerate}
	 \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 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.


\end{enumerate}
}
\headedsection{{\bf Scaling Insight}}{}{


\begin{enumerate}
	 \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 \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 Evgeny Klochikhin and {\bf Jordan Boyd-Graber}.  {\bf Text Analysis}.  \emph{Big Data and Social Science Research: Theory and Practical Approaches}, 2016, 27 pages.

	 \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.


\end{enumerate}
}
\headedsection{{\bf Thinking on Your Feet}}{}{


\begin{enumerate}
	 \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 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}, 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 \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{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 {\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 \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://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 {\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}
}