Jordan L. Boyd-Graber

发表

Leveraging VerbNet to build Corpus-Specific Verb Clusters

Daisuke Kawahara, Daniel W. Peterson, Jordan L. Boyd-Graber, 2016, *SEM@ACL.

Inducing and Embedding Senses with Scaled Gumbel Softmax pdf

Jordan L. Boyd-Graber, Fenfei Guo, Mohit Iyyer, 2018, ArXiv.

Mitigating Noisy Inputs for Question Answering

Graham Neubig, Pedro Rodriguez, Jordan L. Boyd-Graber, 2019, INTERSPEECH.

Online Adaptor Grammars with Hybrid Inference

Shay B. Cohen, Jordan L. Boyd-Graber, Ke Zhai, 2014, Transactions of the Association for Computational Linguistics.

Closing the Loop: User-Centered Design and Evaluation of a Human-in-the-Loop Topic Modeling System

Jordan L. Boyd-Graber, Kevin D. Seppi, Leah Findlater, 2018, IUI.

Right Answer for the Wrong Reason: Discovery and Mitigation pdf

Shi Feng, Eric Wallace, Jordan L. Boyd-Graber, 2018, ArXiv.

Quantifying the role of discourse topicality in speakers’ choices of referring expressions

Naomi Feldman, Naho Orita, Jordan L. Boyd-Graber, 2014, CMCL@ACL.

Speeding Document Annotation with Topic Models

Jordan L. Boyd-Graber, Forough Poursabzi-Sangdeh, Forough Poursabzi-Sangdeh, 2015, NAACL.

Simulating Audiences: Automating Analysis of Values, Attitudes, and Sentiment

Kenneth R. Fleischmann, Jordan L. Boyd-Graber, Thomas Clay Templeton, 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

Making the Most of Crowdsourced Document Annotations: Confused Supervised LDA

Eric K. Ringger, Jordan L. Boyd-Graber, Paul Felt, 2015, CoNLL.

Collecting Semantic Similarity Ratings to Connect Concepts in Assistive Communication Tools

Jordan L. Boyd-Graber, Sonya S. Nikolova, Christiane Fellbaum, 2012, Modeling, Learning, and Processing of Text Technological Data Structures.

Evaluating Visual Representations for Topic Understanding and Their Effects on Manually Generated Topic Labels

Niklas Elmqvist, Jordan L. Boyd-Graber, Forough Poursabzi-Sangdeh, 2017, TACL.

A dataset and baselines for sequential open-domain question answering

Ahmed Elgohary, Jordan L. Boyd-Graber, Chen Zhao, 2018, EMNLP.

Opponent Modeling in Deep Reinforcement Learning

Jordan L. Boyd-Graber, He He, He He, 2016, ICML.

Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation pdf

Shudong Hao, Michael J. Paul, Jordan L. Boyd-Graber, 2018, NAACL.

Meta Answering for Machine Reading pdf

Jannis Bulian, Massimiliano Ciaramita, Rodrigo Nogueira, 2019, ArXiv.

Using Variational Inference and MapReduce to Scale Topic Modeling pdf

Ke Zhai, Jordan L. Boyd-Graber, Nima Asadi, 2011, ArXiv.

Learning from Measurements in Crowdsourcing Models: Inferring Ground Truth from Diverse Annotation Types

Eric K. Ringger, Jordan L. Boyd-Graber, Paul Felt, 2018, COLING.

Modeling Images using Transformed Indian Buffet Processes

Jordan L. Boyd-Graber, Yuening Hu, Ke Zhai, 2012, ICML.

Comparing values and sentiment using Mechanical Turk

Kenneth R. Fleischmann, Jordan L. Boyd-Graber, Thomas Clay Templeton, 2011, iConference '11.

Syntax-based Rewriting for Simultaneous Machine Translation

He He, John Morgan, Hal Daumé, 2015, EMNLP.

Deep Unordered Composition Rivals Syntactic Methods for Text Classification

Hal Daumé, Jordan L. Boyd-Graber, Mohit Iyyer, 2015, ACL.

Anchors Regularized: Adding Robustness and Extensibility to Scalable Topic-Modeling Algorithms

Jordan L. Boyd-Graber, Yuening Hu, Thang Nguyen, 2014, ACL.

Automatic Estimation of Simultaneous Interpreter Performance pdf

Graham Neubig, Nikolai Vogler, Jordan L. Boyd-Graber, 2018, ACL.

A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity

Michael J. Paul, Jordan L. Boyd-Graber, Yoshinari Fujinuma, 2019, ACL.

Speaking through pictures: images vs. icons

Perry R. Cook, Xiaojuan Ma, Jordan L. Boyd-Graber, 2009, Assets '09.

Better vocabularies for assistive communication aids: connecting terms using semantic networks and untrained annotators

Perry R. Cook, Jordan L. Boyd-Graber, Sonya S. Nikolova, 2009, Assets '09.

Polylingual Tree-Based Topic Models for Translation Domain Adaptation

Vladimir Eidelman, Jordan L. Boyd-Graber, Yuening Hu, 2014, ACL.

Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification

Jordan L. Boyd-Graber, Mozhi Zhang, Yoshinari Fujinuma, 2020, AAAI.

Dirichlet Mixtures, the Dirichlet Process, and the Structure of Protein Space

Jordan L. Boyd-Graber, Viet-An Nguyen, Stephen F. Altschul, 2013, J. Comput. Biol..

Interpreting Neural Networks with Nearest Neighbors pdf

Shi Feng, Eric Wallace, Jordan L. Boyd-Graber, 2018, BlackboxNLP@EMNLP.

Why Didn’t You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models

Jordan L. Boyd-Graber, Kevin D. Seppi, Leah Findlater, 2019, ACL.

It Takes Two to Lie: One to Lie, and One to Listen

Cristian Danescu-Niculescu-Mizil, Jordan L. Boyd-Graber, Denis Peskov, 2020, ACL.

Automatic Evaluation of Local Topic Quality pdf

Jordan L. Boyd-Graber, Kevin D. Seppi, Jeffrey Lund, 2019, ACL.

Applications of Topic Models

David M. Mimno, Jordan L. Boyd-Graber, Yuening Hu, 2017, Found. Trends Inf. Retr..

Care and Feeding of Topic Models

David M. Mimno, Jordan L. Boyd-Graber, David Newman, 2014, Handbook of Mixed Membership Models and Their Applications.

Birds of a Feather Linked Together: A Discriminative Topic Model using Link-based Priors

Philip Resnik, Jordan L. Boyd-Graber, Weiwei Yang, 2015, EMNLP.

Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation

He He, Hal Daumé, Jordan L. Boyd-Graber, 2016, NAACL.

Participatory design with proxies: developing a desktop-PDA system to support people with aphasia

Marilyn Tremaine, Jordan L. Boyd-Graber, Maria M. Klawe, 2006, CHI.

Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers

Jordan L. Boyd-Graber, Mohit Iyyer, Anupam Guha, 2015, NAACL.

Beyond LDA: Exploring Supervised Topic Modeling for Depression-Related Language in Twitter

Leonardo Max Batista Claudino, Philip Resnik, Jordan L. Boyd-Graber, 2015, CLPsych@HLT-NAACL.

Spoiler alert: Machine learning approaches to detect social media posts with revelatory information

Jordan L. Boyd-Graber, Kimberly Glasgow, Jackie Sauter Zajac, 2013, ASIST.

Synchronous Machine Translation (NII Shonan Meeting 2015-10)

Yusuke Miyao, Jordan L. Boyd-Graber, Hal Daumé, 2015, NII Shonan Meeting Report.

SITS: A Hierarchical Nonparametric Model using Speaker Identity for Topic Segmentation in Multiparty Conversations

Philip Resnik, Jordan L. Boyd-Graber, Viet-An Nguyen, 2012, ACL.

Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs

Lise Getoor, Bert Huang, Stephen H. Bach, 2015, ICML.

Modeling diverse standpoints in text classification: learning to be human by modeling human values

Kenneth R. Fleischmann, Jordan L. Boyd-Graber, Thomas Clay Templeton, 2011, iConference '11.

Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling

Jordan L. Boyd-Graber, Kevin D. Seppi, Jeffrey Lund, 2017, ACL.

Misleading Failures of Partial-input Baselines

Shi Feng, Eric Wallace, Jordan L. Boyd-Graber, 2019, ACL.

Pathologies of Neural Models Make Interpretations Difficult

Shi Feng, Eric Wallace, Jordan L. Boyd-Graber, 2018, EMNLP.

What Question Answering can Learn from Trivia Nerds pdf

Jordan L. Boyd-Graber, 2020, ACL.

A Discriminative Topic Model using Document Network Structure

Philip Resnik, Jordan L. Boyd-Graber, Weiwei Yang, 2016, ACL.

Why ADAGRAD Fails for Online Topic Modeling

Jordan L. Boyd-Graber, You Lu, Jeffrey Lund, 2017, EMNLP.

The human touch: How non-expert users perceive, interpret, and fix topic models

Niklas Elmqvist, Jordan L. Boyd-Graber, Kevin D. Seppi, 2017, Int. J. Hum. Comput. Stud..

Modeling Perspective Using Adaptor Grammars

Philip Resnik, Jordan L. Boyd-Graber, Eric A. Hardisty, 2010, EMNLP.

A Topic Model for Word Sense Disambiguation

Xiaojin Zhu, David M. Blei, Jordan L. Boyd-Graber, 2007, EMNLP.

What can AI do for me?: evaluating machine learning interpretations in cooperative play

Shi Feng, Jordan L. Boyd-Graber, 2019, IUI.

Believe Me - We Can Do This! Annotating Persuasive Acts in Blog Text

Douglas W. Oard, Philip Resnik, Jordan L. Boyd-Graber, 2011, Computational Models of Natural Argument.

Discovering Pronoun Categories using Discourse Information

Naomi Feldman, Naho Orita, Jordan L. Boyd-Graber, 2013, CogSci.

Learning to Color from Language pdf

Larry S. Davis, Jordan L. Boyd-Graber, Mohit Iyyer, 2018, NAACL.

The design of ViVA: a mixed-initiative visual vocabulary for aphasia

Perry R. Cook, Jordan L. Boyd-Graber, Sonya S. Nikolova, 2009, CHI Extended Abstracts.

Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization pdf

Ken-ichi Kawarabayashi, Stefanie Jegelka, Jordan L. Boyd-Graber, 2019, ACL.

Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation

Hal Daumé, Jordan L. Boyd-Graber, Chen Zhao, 2021, EMNLP.

Toward Deconfounding the Effect of Entity Demographics for Question Answering Accuracy

Jordan L. Boyd-Graber, Kellie Webster, Maharshi Gor, 2021, Conference on Empirical Methods in Natural Language Processing.

Adapting Entities across Languages and Cultures

Jordan L. Boyd-Graber, Denis Peskov, Viktor Hangya, 2021, EMNLP.

Generating Sentences from Semantic Vector Space Representations

Jordan L. Boyd-Graber, Hal Daumé, Mohit Iyyer, 2014 .

Holistic Sentiment Analysis Across Languages: Multilingual Supervised Latent Dirichlet Allocation

Philip Resnik, Jordan Boyd-Graber, Jordan L. Boyd-Graber, 2010, EMNLP.

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

Nicola De Cao, Jordan L. Boyd-Graber, Danqi Chen, 2021, NeurIPS.

Reading Tea Leaves: How Humans Interpret Topic Models

Chong Wang, Sean Gerrish, David M. Blei, 2009, NIPS.

Political Ideology Detection Using Recursive Neural Networks

Philip Resnik, Jordan L. Boyd-Graber, Mohit Iyyer, 2014, ACL.

Models for Dynamic Translation Model Adaptation

Jordan L. Boyd-Graber, P. Resnik, Vladimir Eidelman, 2016 .

Quizbowl: The Case for Incremental Question Answering

Jordan L. Boyd-Graber, Mohit Iyyer, He He, 2019, ArXiv.

Besting the Quiz Master: Crowdsourcing Incremental Classification Games

Jordan L. Boyd-Graber, Jordan Boyd-Graber, He He, 2012, EMNLP.

Connections between the lines: augmenting social networks with text

David M. Blei, Jordan L. Boyd-Graber, Jonathan Chang, 2009, KDD.

Zika discourse in the Americas: A multilingual topic analysis of Twitter

Michael J. Paul, Jordan L. Boyd-Graber, Dasha Pruss, 2019, PloS one.

Old Premise Animals are running New Premise Entailment Hypothesis Animals are outdoors Label

Jordan L. Boyd-Graber, 2019 .

Towards a Discourse Relation-aware Approach for Chinese-english Machine Translation a Mapping-based Approach for General Formal Human Computer Interaction Using Natural Language Learning Grammar with Explicit Annotations for Subordinating Conjunctions Multi-document Summarization Using Distortion-ra

Joel R. Tetreault, Jordan L. Boyd-Graber, Monday, 2022 .

Supplementary Material for Online Adaptor Grammars with Hybrid Inference

Jordan L. Boyd-Graber, K. Zhai, 2014 .

2 Matching Text to Entities : Quiz Bowl

Jordan L. Boyd-Graber, R. Socher, Hal Daumé, 2018 .

Iteration 0 Iteration 5000 Iteration 10000 Iteration 20000

Jordan L. Boyd-Graber, 2017 .

Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships

Jordan L. Boyd-Graber, Hal Daumé, Mohit Iyyer, 2016, NAACL.

Care and Feeding of Topic Models: Problems, Diagnostics, and Improvements

Jordan L. Boyd-Graber, E. Erosheva, 2020 .

12 Care and Feeding of Topic Models : Problems , Diagnostics , and Improvementes

Jordan L. Boyd-Graber, D. Mimno, David M. Mimno, 2014 .

Maximum Likelihood

Jordan L. Boyd-Graber, R. DeSalle, J. Rosenfeld, 2006 .

Label Dependencies using a Tree-structured Hierarchy

Jordan L. Boyd-Graber, P. Resnik, Jonathan Chang, 2018 .

Content Analysis for Values Elicitation

Jordan L. Boyd-Graber, D. Oard, K. Fleischmann, 2012 .

Human-Centered and Interactive: Expanding the Impact of Topic Models

Jordan L. Boyd-Graber, N. Elmqvist, K. Seppi, 2016 .

Measuring discursive influence across scholarship

Jordan L. Boyd-Graber, James A. Evans, D. Blei, 2018, Proceedings of the National Academy of Sciences.

Adaptor Grammars with Hybrid Inference

Shay B. Cohen, Jordan L. Boyd-Graber, K. Zhai, 2018 .

Models for Translation Domain Adaptation

Jordan L. Boyd-Graber, Yuening Hu, K. Zhai, 2018 .

Jordan Boyd-Graber, David Mimno, and David Newman. Care and Feeding of Topic Models: Problems, Diagnostics, and Improvements. Handbook of Mixed Membership Models and Their Applications, 2014.

Edoardo M. Airoldi, Stephen E. Fienberg, Jordan Boyd-Graber, 2014 .

What can AI do for me?: evaluating machine learning interpretations in cooperative play

Jordan L. Boyd-Graber, Shi Feng, 2018, IUI.

Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships

Snigdha Chaturvedi, Hal Daumé, Jordan L. Boyd-Graber, 2016, NAACL.

2 Putting Knowledge in Topic Models

Jordan L. Boyd-Graber, Brianna Satinoff, 2011 .

The Design of ViVA : a MixedInitiative MixedInitiative MixedInitiative Visual Vocabulary for Aphasia

Jordan L. Boyd-Graber, Sonya S. Nikolova, 2018 .

Adding Dense , Weighted Connections to

Jordan L. Boyd-Graber, C. Fellbaum, D. Osherson, 2018 .

Revisiting Calibration for Question Answering

Jordan L. Boyd-Graber, Sewon Min, Chenglei Si, 2022, ArXiv.

Human-Centered Evaluation of Explanations

Jordan L. Boyd-Graber, T. Lombrozo, Q. Liao, 2022, NAACL.

Proceedings of the Workshop on Human-Computer Question Answering

Jordan L. Boyd-Graber, Mohit Iyyer, Jordan Boyd-Graber, 2016 .

A Differentiable Self-disambiguated Sense Embedding Model via Scaled Gumbel Softmax

Jordan Boyd-Graber, Jordan L. Boyd-Graber, Fenfei Guo, 2018 .

Measuring discursive inﬂuence across scholarship

Jordan L. Boyd-Graber, James A. Evans, D. Blei, 2018 .

Prompting GPT-3 To Be Reliable

Jordan L. Boyd-Graber, Zhe Gan, Shuohang Wang, 2022, ICLR.

Re-Examining Calibration: The Case of Question Answering

Jordan L. Boyd-Graber, Chenglei Si, Chen Zhao, 2022, 2205.12507.

Modeling topic control to detect influence in conversations using nonparametric topic models

Jordan L. Boyd-Graber, P. Resnik, Viet-An Nguyen, 2014, Machine Learning.

Interactive topic modeling

Jordan L. Boyd-Graber, Yuening Hu, Brianna Satinoff, 2014, ACL.

What can AI do for me? Evaluating Machine Learning Interpretations in Cooperative Play

Jordan L. Boyd-Graber, 2019 .

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

Nicola De Cao, Jordan L. Boyd-Graber, Danqi Chen, 2021, NeurIPS.

Improving Question Answering with Generation of NQ-like Questions

Jordan L. Boyd-Graber, Saptarashmi Bandyopadhyay, Hao-Li Zou, 2022, ArXiv.

Language Models

Jordan L. Boyd-Graber, Philipp Koehn, 2009, Encyclopedia of Database Systems.

Cheater's Bowl: Human vs. Computer Search Strategies for Open-Domain Question Answering

Jordan L. Boyd-Graber, Andrew Mao, Wanrong He, 2022, ArXiv.

RESEARCH PROPOSAL: EVALUATING AND ENABLING HUMAN–AI COLLABORATION

Jordan L. Boyd-Graber, 2022 .

Cold-start Active Learning through Self-Supervised Language Modeling pdf

Hsuan-Tien Lin, Jordan Boyd-Graber, Jordan L. Boyd-Graber, 2020, EMNLP.

Tea Party in the House: A Hierarchical Ideal Point Topic Model and Its Application to Republican Legislators in the 112th Congress

Philip Resnik, Jordan L. Boyd-Graber, Viet-An Nguyen, 2015, ACL.

Evaluation Paradigms in Question Answering

Jordan Boyd-Graber, Jordan L. Boyd-Graber, Pedro Rodriguez, 2021, EMNLP.

Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent

Jordan L. Boyd-Graber, Jordan Boyd-Graber, Yuening Hu, 2013, NIPS.

No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML

Daniel S. Weld, Jordan L. Boyd-Graber, Leah Findlater, 2020, CHI.

Adapting Coreference Resolution Models through Active Learning

Benjamin Van Durme, Jordan L. Boyd-Graber, Chandler May, 2021, ACL.

Mr. LDA: a flexible large scale topic modeling package using variational inference in MapReduce

Jordan L. Boyd-Graber, Jordan Boyd-Graber, Ke Zhai, 2012, WWW.

Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards?

Jordan Boyd-Graber, Jordan L. Boyd-Graber, John P. Lalor, 2021, ACL.

Automatic Song Translation for Tonal Languages

Jordan L. Boyd-Graber, Zhirui Zhang, Kecheng Zhang, 2022, FINDINGS.

Tensor Robust Principal Component Analysis: Better recovery with atomic norm regularization

Stephen Becker, Jordan L. Boyd-Graber, Derek Driggs, 2019, 1901.10991.

Topic Models for Dynamic Translation Model Adaptation

Vladimir Eidelman, Philip Resnik, Jordan Boyd-Graber, 2012, ACL.

Syntactic Topic Models

David M. Blei, Jordan L. Boyd-Graber, Jordan Boyd-Graber, 2008, NIPS.

Linguistic extensions of topic models

David M. Blei, Jordan L. Boyd-Graber, Jordan Boyd-Graber, 2010 .

Multilingual Topic Models for Unaligned Text pdf

David M. Blei, Jordan L. Boyd-Graber, Jordan Boyd-Graber, 2009, UAI.

Modeling topic control to detect influence in conversations using nonparametric topic models

Philip Resnik, Jordan L. Boyd-Graber, Viet-An Nguyen, 2014, Machine Learning.

What Question Answering can Learn from Trivia Nerds

Jordan L. Boyd-Graber, 2019, ACL.

What’s in a Name? Answer Equivalence For Open-Domain Question Answering pdf

Jordan Boyd-Graber, Jordan L. Boyd-Graber, Chenglei Si, 2021, EMNLP.

On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries pdf

Jordan Boyd-Graber, Jordan L. Boyd-Graber, Chen Zhao, 2020, FINDINGS.

Trick Me If You Can: Human-in-the-Loop Generation of Adversarial Examples for Question Answering

Eric Wallace, Pedro Rodriguez, Shi Feng, 2018, TACL.

Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback pdf

Hal Daumé, Khanh Nguyen, Jordan L. Boyd-Graber, 2017, EMNLP.

Can You Unpack That? Learning to Rewrite Questions-in-Context

Jordan Boyd-Graber, Ahmed Elgohary, Jordan L. Boyd-Graber, 2019, EMNLP.

Linguistic Harbingers of Betrayal: A Case Study on an Online Strategy Game

Cristian Danescu-Niculescu-Mizil, Jordan L. Boyd-Graber, Srijan Kumar, 2015, ACL.

A Neural Network for Factoid Question Answering over Paragraphs

Richard Socher, Hal Daumé, Jordan L. Boyd-Graber, 2014, EMNLP.

Adding dense, weighted connections to WordNet

Jordan L. Boyd-Graber, Jordan Boyd-Graber, Christiane Fellbaum, 2005 .

Learning to Explain Selectively: A Case Study on Question Answering

Jordan L. Boyd-Graber, Shi Feng, 2022, EMNLP.

Efficient Methods for Incorporating Knowledge into Topic Models

Doug Downey, Jordan L. Boyd-Graber, Yi Yang, 2015, EMNLP.

Fool Me Twice: Entailment from Wikipedia Gamification

Jordan L. Boyd-Graber, Julian Martin Eisenschlos, Jannis Bulian, 2021, NAACL.

CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims pdf

Jannis Bulian, Jordan Boyd-Graber, Massimiliano Ciaramita, 2020, ArXiv.

Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval pdf

Jordan Boyd-Graber, Chenyan Xiong, Jordan L. Boyd-Graber, 2021, NAACL.

Don't Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation

Jordan L. Boyd-Graber, Jordan Boyd-Graber, He He, 2014, EMNLP.

Modeling topic control to detect influence in conversations using nonparametric topic models

Jordan L. Boyd-Graber, P. Resnik, Viet-An Nguyen, 2013, Machine Learning.

A Multilingual Topic Model for Learning Weighted Topic Links Across Corpora with Low Comparability

Philip Resnik, Jordan L. Boyd-Graber, Weiwei Yang, 2019, EMNLP.

The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives

Larry S. Davis, Jordan L. Boyd-Graber, Mohit Iyyer, 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence pdf

Philip Resnik, Jordan Boyd-Graber, Jordan L. Boyd-Graber, 2021, NeurIPS.

Mixture of Prompt Experts for Generalizable and Interpretable Question Answering

Jordan L. Boyd-Graber, Luke Zettlemoyer, Luke Zettlemoyer, 2023, ArXiv.

Bayesian Supervised Domain Adaptation for Short Text Similarity

Tamara Sumner, Jordan L. Boyd-Graber, Jordan Boyd-Graber, 2016, NAACL.

What can AI do for me?: evaluating machine learning interpretations in cooperative play

Jordan L. Boyd-Graber, Shi Feng, 2018, IUI.

Grammatical structures for word-level sentiment detection

Jordan L. Boyd-Graber, Amy Weinberg, Asad B. Sayeed, 2012, NAACL.

Adaptive Active Learning for Coreference Resolution pdf

Jordan Boyd-Graber, Benjamin Van Durme, Jordan L. Boyd-Graber, 2021, ArXiv.

"Our Grief is Unspeakable": Automatically Measuring the Community Impact of a Tragedy

Jordan L. Boyd-Graber, Clayton Fink, Jordan Boyd-Graber, 2014, ICWSM.

Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling

Jordan L. Boyd-Graber, Jeffrey Lund, C. Cook, 2017, ACL.

Efficient Tree-Based Topic Modeling

Jordan L. Boyd-Graber, Jordan Boyd-Graber, Yuening Hu, 2012, ACL.

Is Your Anchor Going Up or Down? Fast and Accurate Supervised Topic Models

Thang Nguyen, Eric K. Ringger, Jordan L. Boyd-Graber, 2015, NAACL.

Interactive topic modeling

Jordan L. Boyd-Graber, Yuening Hu, Alison Smith, 2014, ACL.

Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation pdf

Chenyan Xiong, Hal Daumé, Jordan L. Boyd-Graber, 2021, EMNLP.

Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions pdf

Jordan Boyd-Graber, Jordan L. Boyd-Graber, Eric Wallace, 2018, ACL.

Towards Deconfounding the Influence of Subject's Demographic Characteristics in Question Answering pdf

Jordan Boyd-Graber, Jordan L. Boyd-Graber, Kellie Webster, 2021, ArXiv.

Trick Me If You Can: Human-in-the-loop Generation of Adversarial Question Answering Examples

Shi Feng, Ikuya Yamada, Jordan L. Boyd-Graber, 2019, Trans. Assoc. Comput. Linguistics.

Evaluating Visual Representations for Topic Understanding and Their Effects on Manually Generated Topic Labels

Jordan L. Boyd-Graber, N. Elmqvist, Forough Poursabzi-Sangdeh, 2017 .

Meta Answering for Machine Reading

Jordan L. Boyd-Graber, Lierni Sestorain Saralegu, Michelle Chen Huebscher, 2019, ArXiv.

Online Latent Dirichlet Allocation with Infinite Vocabulary

Jordan Boyd-Graber, Jordan L. Boyd-Graber, Ke Zhai, 2013, ICML.

Latent Dirichlet Allocation with Infinite Vocabulary

Jordan Boyd-Graber, Jordan L. Boyd-Graber, 2016 .

Frameworks

Jordan L. Boyd-Graber, Chris Dyer, Graham Neubig, 2021, Seamus Heaney in Context.

A Neural Network for Factoid Question Answering over Paragraphs

Jordan L. Boyd-Graber, R. Socher, Hal Daumé, 2014, EMNLP.

Using Confusion Graphs to Understand Classifier Error

Jordan Boyd-Graber, Jordan L. Boyd-Graber, Davis Yoshida, 2016 .

Interactive Topic Modeling

Jordan L. Boyd-Graber, Yuening Hu, Brianna Satinoff, 2011, ACL.

Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling

Jordan L. Boyd-Graber, Jeffrey Lund, C. Cook, 2017, Annual Meeting of the Association for Computational Linguistics.

ALTO: Active Learning with Topic Overviews for Speeding Label Induction and Document Labeling

Jordan L. Boyd-Graber, Kevin Seppi, Leah Findlater, 2016, ACL.

Concurrent Visualization of Relationships between Words and Topics in Topic Models

Jordan Boyd-Graber, Jordan L. Boyd-Graber, Jason Chuang, 2014 .

Interactive topic modeling

Jordan L. Boyd-Graber, Yuening Hu, Brianna Satinoff, 2013, Machine Learning.

Argviz: Interactive Visualization of Topic Dynamics in Multi-party Conversations

Philip Resnik, Jordan L. Boyd-Graber, Viet-An Nguyen, 2013, NAACL.

Evaluating Visual Representations for Topic Understanding and Their Effects on Manually Generated Topic Labels

Jordan L. Boyd-Graber, Tak Yeon Lee, N. Elmqvist, 2019 .

Topic Models for Translation Domain Adaptation

Jordan Boyd-Graber, Jordan L. Boyd-Graber, Yuening Hu, 2013 .

BYU ScholarsArchive BYU ScholarsArchive

Jordan L. Boyd-Graber, N. Elmqvist, Alison Smith, 2022 .

Match the Script, Adapt if Multilingual: Analyzing the Effect of Multilingual Pretraining on Cross-lingual Transferability

Jordan L. Boyd-Graber, Yoshinari Fujinuma, Katharina Kann, 2022, ACL.

Reading Tea Leaves: How Humans Interpret Topic Models

Jordan L. Boyd-Graber, Jonathan D. Chang, D. Blei, 2009, NIPS.

Speaking through pictures: images vs. icons

Jordan L. Boyd-Graber, Sonya S. Nikolova, Xiaojuan Ma, 2009, Assets '09.

Learning Text Pair Similarity with Context-sensitive Autoencoders

Philip Resnik, Jordan L. Boyd-Graber, Jordan Boyd-Graber, 2016, ACL.

2 Matching Text to Entities : Quiz Bowl

Jordan L. Boyd-Graber, R. Socher, Hal Daumé, 2017 .

2 Matching Text to Entities : Quiz Bowl

Jordan L. Boyd-Graber, R. Socher, Hal Daumé, 2016 .

2 Matching Text to Entities : Quiz Bowl

Jordan L. Boyd-Graber, R. Socher, Hal Daumé, 2015 .

Discovering Pronoun Categories using Discourse Information

Jordan L. Boyd-Graber, Naho Orita, Naomi H Feldman, 2013, CogSci.

Participatory design with proxies: developing a desktop-PDA system to support people with aphasia

Jordan L. Boyd-Graber, Sonya S. Nikolova, M. Klawe, 2006, CHI.

Language Models

Jordan L. Boyd-Graber, Philipp Koehn, 2009, Encyclopedia of Database Systems.

Reading Tea Leaves: How Humans Interpret Topic Models

Jordan L. Boyd-Graber, Jonathan D. Chang, D. Blei, 2009, NIPS.

What can AI do for me? Evaluating Machine Learning Interpretations in Cooperative Play

Jordan L. Boyd-Graber, 2019 .

InteractiveIE: Towards Assessing the Strength of Human-AI Collaboration in Improving the Performance of Information Extraction

Benjamin Van Durme, Jordan L. Boyd-Graber, Francis Ferraro, 2023, ArXiv.

Speaking through pictures: images vs. icons

Jordan L. Boyd-Graber, Sonya S. Nikolova, Xiaojuan Ma, 2009, Assets '09.

ClimaText: A Dataset for Climate Change Topic Detection

Jordan L. Boyd-Graber, Francesco S. Varini, Massimiliano Ciaramita, 2020, ArXiv.

Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships

Jordan L. Boyd-Graber, Hal Daumé, Mohit Iyyer, 2016, NAACL.

Deep Unordered Composition Rivals Syntactic Methods for Text Classification

Jordan L. Boyd-Graber, Hal Daumé, Mohit Iyyer, 2015, ACL.

Adding dense, weighted connections to WordNet

Jordan L. Boyd-Graber, R. Schapire, C. Fellbaum, 2005 .

Modeling Perspective Using Adaptor Grammars

Jordan L. Boyd-Graber, Eric A. Hardisty, P. Resnik, 2010, EMNLP.

Sometimes Average is Best: The Importance of Averaging for Prediction using MCMC Inference in Topic Modeling

Jordan L. Boyd-Graber, P. Resnik, Viet-An Nguyen, 2014, EMNLP.

Anchors Regularized: Adding Robustness and Extensibility to Scalable Topic-Modeling Algorithms

Jordan L. Boyd-Graber, Yuening Hu, Thang Nguyen, 2014, ACL.

Is Your Anchor Going Up or Down? Fast and Accurate Supervised Topic Models

Eric K. Ringger, Jordan L. Boyd-Graber, Jeffrey Lund, 2015, NAACL.

Why Overfitting Isn’t Always Bad: Retrofitting Cross-Lingual Word Embeddings to Dictionaries

Michael J. Paul, Jordan L. Boyd-Graber, Mozhi Zhang, 2020, ACL.

Mr. LDA: a flexible large scale topic modeling package using variational inference in MapReduce

Jordan L. Boyd-Graber, K. Zhai, N. Asadi, 2012, WWW.

Linguistic Harbingers of Betrayal: A Case Study on an Online Strategy Game

Jordan L. Boyd-Graber, Srijan Kumar, Cristian Danescu-Niculescu-Mizil, 2015, ACL.

Hybrid Online Inference with Adaptor Grammars

Ke Zhai, Shay B. Cohen, Jordan L. Boyd-Graber, 2014 .