| 2024 | ACL | More Victories, Less Cooperation: Assessing Cicero's Diplomacy Play. | Wichayaporn Wongkamjan, Feng Gu, Yanze Wang, Ulf Hermjakob, Jonathan May, Brandon M. Stewart, Jonathan K. Kummerfeld, Denis Peskoff, Jordan L. Boyd-Graber |
| 2024 | COLING | Rapidly Piloting Real-time Linguistic Assistance for Simultaneous Interpreters with Untrained Bilingual Surrogates. | Alvin Grissom II, Jo Shoemaker, Benjamin Goldman, Ruikang Shi, Craig Stewart, C. Anton Rytting, Leah Findlater, Jordan L. Boyd-Graber |
| 2024 | EACL | Improving the TENOR of Labeling: Re-evaluating Topic Models for Content Analysis. | Zongxia Li, Andrew Mao, Daniel Kofi Stephens, Pranav Goel, Emily Walpole, Alden Dima, Juan Fung, Jordan L. Boyd-Graber |
| 2024 | EACL | Presentations by the Humans and For the Humans: Harnessing LLMs for Generating Persona-Aware Slides from Documents. | Ishani Mondal, Shwetha S, Anandhavelu Natarajan, Aparna Garimella, Sambaran Bandyopadhyay, Jordan L. Boyd-Graber |
| 2024 | EMNLP | A SMART Mnemonic Sounds like "Glue Tonic": Mixing LLMs with Student Feedback to Make Mnemonic Learning Stick. | Nishant Balepur, Matthew Shu, Alexander Miserlis Hoyle, Alison Robey, Shi Feng, Seraphina Goldfarb-Tarrant, Jordan L. Boyd-Graber |
| 2024 | EMNLP | Do great minds think alike? Investigating Human-AI Complementarity in Question Answering with CAIMIRA. | Maharshi Gor, Hal Daum III, Tianyi Zhou, Jordan L. Boyd-Graber |
| 2024 | EMNLP | You Make me Feel like a Natural Question: Training QA Systems on Transformed Trivia Questions. | Tasnim Kabir, Yoo Yeon Sung, Saptarashmi Bandyopadhyay, Hao Zou, Abhranil Chandra, Jordan L. Boyd-Graber |
| 2024 | EMNLP | PEDANTS: Cheap but Effective and Interpretable Answer Equivalence. | Zongxia Li, Ishani Mondal, Huy Nghiem, Yijun Liang, Jordan L. Boyd-Graber |
| 2024 | EMNLP | SciDoc2Diagrammer-MAF: Towards Generation of Scientific Diagrams from Documents guided by Multi-Aspect Feedback Refinement. | Ishani Mondal, Zongxia Li, Yufang Hou, Anandhavelu Natarajan, Aparna Garimella, Jordan L. Boyd-Graber |
| 2024 | EMNLP | KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students. | Matthew Shu, Nishant Balepur, Shi Feng, Jordan L. Boyd-Graber |
| 2024 | EMNLP | AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models. | Xiyang Wu, Tianrui Guan, Dianqi Li, Shuaiyi Huang, Xiaoyu Liu, Xijun Wang, Ruiqi Xian, Abhinav Shrivastava, Furong Huang, Jordan L. Boyd-Graber, Tianyi Zhou, Dinesh Manocha |
| 2024 | NAACL | Large Language Models Help Humans Verify Truthfulness - Except When They Are Convincingly Wrong. | Chenglei Si, Navita Goyal, Tongshuang Wu, Chen Zhao, Shi Feng, Hal Daum III, Jordan L. Boyd-Graber |
| 2024 | NAACL | Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering. | Neha Srikanth, Rupak Sarkar, Heran Mane, Elizabeth Aparicio, Quynh C. Nguyen, Rachel Rudinger, Jordan L. Boyd-Graber |
| 2023 | EMNLP | Bridging Background Knowledge Gaps in Translation with Automatic Explicitation. | HyoJung Han, Jordan L. Boyd-Graber, Marine Carpuat |
| 2023 | EMNLP | Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs Through a Global Prompt Hacking Competition. | Sander Schulhoff, Jeremy Pinto, Anaum Khan, Louis-Franois Bouchard, Chenglei Si, Svetlina Anati, Valen Tagliabue, Anson Liu Kost, Christopher Carnahan, Jordan L. Boyd-Graber |
| 2023 | EMNLP | Getting MoRE out of Mixture of Language Model Reasoning Experts. | Chenglei Si, Weijia Shi, Chen Zhao, Luke Zettlemoyer, Jordan L. Boyd-Graber |
| 2023 | EMNLP | Not all Fake News is Written: A Dataset and Analysis of Misleading Video Headlines. | Yoo Yeon Sung, Jordan L. Boyd-Graber, Naeemul Hassan |
| 2023 | ICLR | Prompting GPT-3 To Be Reliable. | Chenglei Si, Zhe Gan, Zhengyuan Yang, Shuohang Wang, Jianfeng Wang, Jordan L. Boyd-Graber, Lijuan Wang |
| 2022 | ACL | Match the Script, Adapt if Multilingual: Analyzing the Effect of Multilingual Pretraining on Cross-lingual Transferability. | Yoshinari Fujinuma, Jordan L. Boyd-Graber, Katharina Kann |
| 2022 | ACL | Automatic Song Translation for Tonal Languages. | Fenfei Guo, Chen Zhang, Zhirui Zhang, Qixin He, Kejun Zhang, Jun Xie, Jordan L. Boyd-Graber |
| 2022 | ACL | Adapting Coreference Resolution Models through Active Learning. | Michelle Yuan, Patrick Xia, Chandler May, Benjamin Van Durme, Jordan L. Boyd-Graber |
| 2022 | EMNLP | Learning to Explain Selectively: A Case Study on Question Answering. | Shi Feng, Jordan L. Boyd-Graber |
| 2022 | EMNLP | SimQA: Detecting Simultaneous MT Errors through Word-by-Word Question Answering. | HyoJung Han, Marine Carpuat, Jordan L. Boyd-Graber |
| 2022 | EMNLP | Cheater's Bowl: Human vs. Computer Search Strategies for Open-Domain QA. | Wanrong He, Andrew Mao, Jordan L. Boyd-Graber |
| 2022 | EMNLP | Re-Examining Calibration: The Case of Question Answering. | Chenglei Si, Chen Zhao, Sewon Min, Jordan L. Boyd-Graber |
| 2021 | ACL | Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards? | Pedro Rodriguez, Joe Barrow, Alexander Miserlis Hoyle, John P. Lalor, Robin Jia, Jordan L. Boyd-Graber |
| 2021 | EMNLP | Toward Deconfounding the Effect of Entity Demographics for Question Answering Accuracy. | Maharshi Gor, Kellie Webster, Jordan L. Boyd-Graber |
| 2021 | EMNLP | Adapting Entities across Languages and Cultures. | Denis Peskov, Viktor Hangya, Jordan L. Boyd-Graber, Alexander Fraser |
| 2021 | EMNLP | Evaluation Paradigms in Question Answering. | Pedro Rodriguez, Jordan L. Boyd-Graber |
| 2021 | EMNLP | What's in a Name? Answer Equivalence For Open-Domain Question Answering. | Chenglei Si, Chen Zhao, Jordan L. Boyd-Graber |
| 2021 | EMNLP | Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation. | Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daum III |
| 2021 | NAACL | Fool Me Twice: Entailment from Wikipedia Gamification. | Julian Martin Eisenschlos, Bhuwan Dhingra, Jannis Bulian, Benjamin Brschinger, Jordan L. Boyd-Graber |
| 2021 | NAACL | Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval. | Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daum III |
| 2020 | AAAI | Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification. | Mozhi Zhang, Yoshinari Fujinuma, Jordan L. Boyd-Graber |
| 2020 | ACL | What Question Answering can Learn from Trivia Nerds. | Jordan L. Boyd-Graber, Benjamin Brschinger |
| 2020 | ACL | It Takes Two to Lie: One to Lie, and One to Listen. | Denis Peskov, Benny Cheng, Ahmed Elgohary, Joe Barrow, Cristian Danescu-Niculescu-Mizil, Jordan L. Boyd-Graber |
| 2020 | ACL | Why Overfitting Isn't Always Bad: Retrofitting Cross-Lingual Word Embeddings to Dictionaries. | Mozhi Zhang, Yoshinari Fujinuma, Michael J. Paul, Jordan L. Boyd-Graber |
| 2020 | CHI | No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML. | Alison Smith-Renner, Ron Fan, Melissa Birchfield, Tongshuang Wu, Jordan L. Boyd-Graber, Daniel S. Weld, Leah Findlater |
| 2020 | EMNLP | An Attentive Recurrent Model for Incremental Prediction of Sentence-final Verbs. | Wenyan Li, Alvin Grissom II, Jordan L. Boyd-Graber |
| 2020 | EMNLP | On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries. | Tianze Shi, Chen Zhao, Jordan L. Boyd-Graber, Hal Daum III, Lillian Lee |
| 2020 | EMNLP | Cold-start Active Learning through Self-supervised Language Modeling. | Michelle Yuan, Hsuan-Tien Lin, Jordan L. Boyd-Graber |
| 2020 | EMNLP | Interactive Refinement of Cross-Lingual Word Embeddings. | Michelle Yuan, Mozhi Zhang, Benjamin Van Durme, Leah Findlater, Jordan L. Boyd-Graber |
| 2020 | IUI | Digging into user control: perceptions of adherence and instability in transparent models. | Alison Smith-Renner, Varun Kumar, Jordan L. Boyd-Graber, Kevin D. Seppi, Leah Findlater |
| 2020 | LREC | Which Evaluations Uncover Sense Representations that Actually Make Sense? | Jordan L. Boyd-Graber, Fenfei Guo, Leah Findlater, Mohit Iyyer |
| 2020 | WWW | Complex Factoid Question Answering with a Free-Text Knowledge Graph. | Chen Zhao, Chenyan Xiong, Xin Qian, Jordan L. Boyd-Graber |
| 2019 | ACL | Misleading Failures of Partial-input Baselines. | Shi Feng, Eric Wallace, Jordan L. Boyd-Graber |
| 2019 | ACL | A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity. | Yoshinari Fujinuma, Jordan L. Boyd-Graber, Michael J. Paul |
| 2019 | ACL | Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models. | Varun Kumar, Alison Smith-Renner, Leah Findlater, Kevin D. Seppi, Jordan L. Boyd-Graber |
| 2019 | ACL | Automatic Evaluation of Local Topic Quality. | Jeffrey Lund, Piper Armstrong, Wilson Fearn, Stephen Cowley, Courtni Byun, Jordan L. Boyd-Graber, Kevin D. Seppi |
| 2019 | ACL | Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization. | Mozhi Zhang, Keyulu Xu, Ken-ichi Kawarabayashi, Stefanie Jegelka, Jordan L. Boyd-Graber |
| 2019 | EMNLP | Can You Unpack That? Learning to Rewrite Questions-in-Context. | Ahmed Elgohary, Denis Peskov, Jordan L. Boyd-Graber |
| 2019 | EMNLP | A Multilingual Topic Model for Learning Weighted Topic Links Across Corpora with Low Comparability. | Weiwei Yang, Jordan L. Boyd-Graber, Philip Resnik |
| 2019 | Interspeech | Mitigating Noisy Inputs for Question Answering. | Denis Peskov, Joe Barrow, Pedro Rodriguez, Graham Neubig, Jordan L. Boyd-Graber |
| 2019 | IUI | What can AI do for me?: evaluating machine learning interpretations in cooperative play. | Shi Feng, Jordan L. Boyd-Graber |
| 2018 | ACL | Automatic Estimation of Simultaneous Interpreter Performance. | Craig Stewart, Nikolai Vogler, Junjie Hu, Jordan L. Boyd-Graber, Graham Neubig |
| 2018 | ACL | Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions. | Eric Wallace, Jordan L. Boyd-Graber |
| 2018 | COLING | Learning from Measurements in Crowdsourcing Models: Inferring Ground Truth from Diverse Annotation Types. | Paul Felt, Eric K. Ringger, Jordan L. Boyd-Graber, Kevin D. Seppi |
| 2018 | EMNLP | A dataset and baselines for sequential open-domain question answering. | Ahmed Elgohary, Chen Zhao, Jordan L. Boyd-Graber |
| 2018 | EMNLP | Pathologies of Neural Models Make Interpretation Difficult. | Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, Jordan L. Boyd-Graber |
| 2018 | EMNLP | Interpreting Neural Networks with Nearest Neighbors. | Eric Wallace, Shi Feng, Jordan L. Boyd-Graber |
| 2018 | IUI | Closing the Loop: User-Centered Design and Evaluation of a Human-in-the-Loop Topic Modeling System. | Alison Smith, Varun Kumar, Jordan L. Boyd-Graber, Kevin D. Seppi, Leah Findlater |
| 2018 | NAACL | Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation. | Shudong Hao, Jordan L. Boyd-Graber, Michael J. Paul |
| 2018 | NAACL | Learning to Color from Language. | Varun Manjunatha, Mohit Iyyer, Jordan L. Boyd-Graber, Larry S. Davis |
| 2017 | ACL | Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling. | Jeffrey Lund, Connor Cook, Kevin D. Seppi, Jordan L. Boyd-Graber |
| 2017 | CVPR | The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives. | Mohit Iyyer, Varun Manjunatha, Anupam Guha, Yogarshi Vyas, Jordan L. Boyd-Graber, Hal Daum III, Larry S. Davis |
| 2017 | EMNLP | Why ADAGRAD Fails for Online Topic Modeling. | You Lu, Jeffrey Lund, Jordan L. Boyd-Graber |
| 2017 | EMNLP | Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback. | Khanh Nguyen, Hal Daum III, Jordan L. Boyd-Graber |
| 2017 | EMNLP | Adapting Topic Models using Lexical Associations with Tree Priors. | Weiwei Yang, Jordan L. Boyd-Graber, Philip Resnik |
| 2016 | ACL | Learning Text Pair Similarity with Context-sensitive Autoencoders. | Hadi Amiri, Philip Resnik, Jordan L. Boyd-Graber, Hal Daum III |
| 2016 | ACL | ALTO: Active Learning with Topic Overviews for Speeding Label Induction and Document Labeling. | Forough Poursabzi-Sangdeh, Jordan L. Boyd-Graber, Leah Findlater, Kevin D. Seppi |
| 2016 | ACL | A Discriminative Topic Model using Document Network Structure. | Weiwei Yang, Jordan L. Boyd-Graber, Philip Resnik |
| 2016 | CoNLL | Incremental Prediction of Sentence-final Verbs: Humans versus Machines. | Alvin Grissom II, Naho Orita, Jordan L. Boyd-Graber |
| 2016 | ICML | Opponent Modeling in Deep Reinforcement Learning. | He He, Jordan L. Boyd-Graber |
| 2016 | NAACL | Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation. | He He, Jordan L. Boyd-Graber, Hal Daum III |
| 2016 | NAACL | Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships. | Mohit Iyyer, Anupam Guha, Snigdha Chaturvedi, Jordan L. Boyd-Graber, Hal Daum III |
| 2016 | NAACL | Bayesian Supervised Domain Adaptation for Short Text Similarity. | Md. Arafat Sultan, Jordan L. Boyd-Graber, Tamara Sumner |
| 2015 | ACL | Deep Unordered Composition Rivals Syntactic Methods for Text Classification. | Mohit Iyyer, Varun Manjunatha, Jordan L. Boyd-Graber, Hal Daum III |
| 2015 | ACL | Tea Party in the House: A Hierarchical Ideal Point Topic Model and Its Application to Republican Legislators in the 112th Congress. | Viet-An Nguyen, Jordan L. Boyd-Graber, Philip Resnik, Kristina Miler |
| 2015 | ACL | Linguistic Harbingers of Betrayal: A Case Study on an Online Strategy Game. | Vlad Niculae, Srijan Kumar, Jordan L. Boyd-Graber, Cristian Danescu-Niculescu-Mizil |
| 2015 | CoNLL | Making the Most of Crowdsourced Document Annotations: Confused Supervised LDA. | Paul Felt, Eric K. Ringger, Jordan L. Boyd-Graber, Kevin D. Seppi |
| 2015 | EMNLP | Syntax-based Rewriting for Simultaneous Machine Translation. | He He, Alvin Grissom II, John Morgan, Jordan L. Boyd-Graber, Hal Daum III |
| 2015 | EMNLP | Birds of a Feather Linked Together: A Discriminative Topic Model using Link-based Priors. | Weiwei Yang, Jordan L. Boyd-Graber, Philip Resnik |
| 2015 | EMNLP | Efficient Methods for Incorporating Knowledge into Topic Models. | Yi Yang, Doug Downey, Jordan L. Boyd-Graber |
| 2015 | ICML | Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs. | Stephen H. Bach, Bert Huang, Jordan L. Boyd-Graber, Lise Getoor |
| 2015 | NAACL | Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers. | Anupam Guha, Mohit Iyyer, Danny Bouman, Jordan L. Boyd-Graber |
| 2015 | NAACL | Is Your Anchor Going Up or Down? Fast and Accurate Supervised Topic Models. | Thang Nguyen, Jordan L. Boyd-Graber, Jeffrey Lund, Kevin D. Seppi, Eric K. Ringger |
| 2015 | NAACL | Speeding Document Annotation with Topic Models. | Forough Poursabzi-Sangdeh, Jordan L. Boyd-Graber |
| 2015 | NAACL | Beyond LDA: Exploring Supervised Topic Modeling for Depression-Related Language in Twitter. | Philip Resnik, William Armstrong, Leonardo Max Batista Claudino, Thang Nguyen, Viet-An Nguyen, Jordan L. Boyd-Graber |
| 2014 | ACL | Polylingual Tree-Based Topic Models for Translation Domain Adaptation. | Yuening Hu, Ke Zhai, Vladimir Eidelman, Jordan L. Boyd-Graber |
| 2014 | ACL | Political Ideology Detection Using Recursive Neural Networks. | Mohit Iyyer, Peter Enns, Jordan L. Boyd-Graber, Philip Resnik |
| 2014 | ACL | Anchors Regularized: Adding Robustness and Extensibility to Scalable Topic-Modeling Algorithms. | Thang Nguyen, Yuening Hu, Jordan L. Boyd-Graber |
| 2014 | EMNLP | Don't Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation. | Alvin Grissom II, He He, Jordan L. Boyd-Graber, John Morgan, Hal Daum III |
| 2014 | EMNLP | A Neural Network for Factoid Question Answering over Paragraphs. | Mohit Iyyer, Jordan L. Boyd-Graber, Leonardo Max Batista Claudino, Richard Socher, Hal Daum III |
| 2014 | EMNLP | Sometimes Average is Best: The Importance of Averaging for Prediction using MCMC Inference in Topic Modeling. | Viet-An Nguyen, Jordan L. Boyd-Graber, Philip Resnik |
| 2014 | ICWSM | "Our Grief is Unspeakable": Automatically Measuring the Community Impact of a Tragedy. | Kimberly Glasgow, Clayton Fink, Jordan L. Boyd-Graber |
| 2013 | CogSci | Discovering Pronoun Categories using Discourse Information. | Naho Orita, Rebecca McKeown, Naomi Feldman, Jeffrey Lidz, Jordan L. Boyd-Graber |
| 2013 | ICML | Online Latent Dirichlet Allocation with Infinite Vocabulary. | Ke Zhai, Jordan L. Boyd-Graber |
| 2013 | NAACL | Argviz: Interactive Visualization of Topic Dynamics in Multi-party Conversations. | Viet-An Nguyen, Yuening Hu, Jordan L. Boyd-Graber, Philip Resnik |
| 2012 | ACL | Topic Models for Dynamic Translation Model Adaptation. | Vladimir Eidelman, Jordan L. Boyd-Graber, Philip Resnik |
| 2012 | ACL | Efficient Tree-Based Topic Modeling. | Yuening Hu, Jordan L. Boyd-Graber |
| 2012 | ACL | SITS: A Hierarchical Nonparametric Model using Speaker Identity for Topic Segmentation in Multiparty Conversations. | Viet-An Nguyen, Jordan L. Boyd-Graber, Philip Resnik |
| 2012 | EMNLP | Besting the Quiz Master: Crowdsourcing Incremental Classification Games. | Jordan L. Boyd-Graber, Brianna Satinoff, He He, Hal Daum III |
| 2012 | ICML | Modeling Images using Transformed Indian Buffet Processes. | Ke Zhai, Yuening Hu, Jordan L. Boyd-Graber, Sinead Williamson |
| 2012 | NAACL | Grammatical structures for word-level sentiment detection. | Asad B. Sayeed, Jordan L. Boyd-Graber, Bryan Rusk, Amy Weinberg |
| 2012 | WWW | Mr. LDA: a flexible large scale topic modeling package using variational inference in MapReduce. | Ke Zhai, Jordan L. Boyd-Graber, Sebastian Bruch, Mohamad L. Alkhouja |
| 2011 | AAAI | Believe Me - We Can Do This! Annotating Persuasive Acts in Blog Text. | Pranav Anand, Joseph King, Jordan L. Boyd-Graber, Earl Wagner, Craig H. Martell, Douglas W. Oard, Philip Resnik |
| 2011 | ACL | Interactive Topic Modeling. | Yuening Hu, Jordan L. Boyd-Graber, Brianna Satinoff |
| 2010 | EMNLP | Holistic Sentiment Analysis Across Languages: Multilingual Supervised Latent Dirichlet Allocation. | Jordan L. Boyd-Graber, Philip Resnik |
| 2010 | EMNLP | Modeling Perspective Using Adaptor Grammars. | Eric Hardisty, Jordan L. Boyd-Graber, Philip Resnik |
| 2010 | NAACL | Measuring Transitivity Using Untrained Annotators. | Nitin Madnani, Jordan L. Boyd-Graber, Philip Resnik |
| 2009 | ASSETS | Speaking through pictures: images vs. icons. | Xiaojuan Ma, Jordan L. Boyd-Graber, Sonya S. Nikolova, Perry R. Cook |
| 2009 | ASSETS | Better vocabularies for assistive communication aids: connecting terms using semantic networks and untrained annotators. | Sonya S. Nikolova, Jordan L. Boyd-Graber, Christiane Fellbaum, Perry R. Cook |
| 2009 | CHI | The design of ViVA: a mixed-initiative visual vocabulary for aphasia. | Sonya S. Nikolova, Jordan L. Boyd-Graber, Perry R. Cook |
| 2009 | KDD | Connections between the lines: augmenting social networks with text. | Jonathan D. Chang, Jordan L. Boyd-Graber, David M. Blei |
| 2009 | UAI | Multilingual Topic Models for Unaligned Text. | Jordan L. Boyd-Graber, David M. Blei |
| 2007 | EMNLP | A Topic Model for Word Sense Disambiguation. | Jordan L. Boyd-Graber, David M. Blei, Xiaojin Zhu |
| 2006 | CHI | Participatory design with proxies: developing a desktop-PDA system to support people with aphasia. | Jordan L. Boyd-Graber, Sonya S. Nikolova, Karyn Moffatt, Kenrick C. Kin, Joshua Y. Lee, Lester W. Mackey, Marilyn Tremaine, Maria M. Klawe |