Jordan Boyd-Graber: Pubs (Project)

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Adaptive Heads-up Displays for Simultaneous Interpretation

Craig Stewart, Nikolai Vogler, Junjie Hu, Jordan Boyd-Graber, and Graham Neubig. Automatic Estimation of Simultaneous Interpreter Performance. Association for Computational Linguistics, 2018. [Bibtex]

@inproceedings{Stewart:Vogler:Hu:Boyd-Graber:Neubig-2018,
	Author = {Craig Stewart and Nikolai Vogler and Junjie Hu and Jordan Boyd-Graber and Graham Neubig},
	Url = {docs/2018_acl_interpeval.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Melbourne, Australia},
	Year = {2018},
	Title = {Automatic Estimation of Simultaneous Interpreter Performance},
}

CAREER

Shi Feng and Jordan Boyd-Graber. What AI can do for me: Evaluating Machine Learning Interpretations in Cooperative Play. Intelligent User Interfaces, 2019. [Bibtex]

@inproceedings{Feng:Boyd-Graber-2019,
	Author = {Shi Feng and Jordan Boyd-Graber},
	Url = {docs/2019_iui_augment.pdf},
	Booktitle = {Intelligent User Interfaces},
	Location = {Los Angeles, CA},
	Year = {2019},
	Title = {What AI can do for me: Evaluating Machine Learning Interpretations in Cooperative Play},
}

Eric Wallace and Jordan Boyd-Graber. Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions. ACL Student Research Workshop, 2018. [Bibtex]

@inproceedings{Wallace:Boyd-Graber-2018,
	Author = {Eric Wallace and Jordan Boyd-Graber},
	Url = {http://aclweb.org/anthology/P18-3018},
	Booktitle = {ACL Student Research Workshop},
	Location = {Melbourne, Australia},
	Year = {2018},
	Title = {Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions},
}

Ahmed Elgohary, Chen Zhao, and Jordan Boyd-Graber. Dataset and Baselines for Sequential Open-Domain Question Answering. Empirical Methods in Natural Language Processing, 2018. [Bibtex]

@inproceedings{Elgohary:Zhao:Boyd-Graber-2018,
	Author = {Ahmed Elgohary and Chen Zhao and Jordan Boyd-Graber},
	Url = {docs/2018_emnlp_linked.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Location = {Brussels, Belgium},
	Year = {2018},
	Title = {Dataset and Baselines for Sequential Open-Domain Question Answering},
}

Shi Feng, Eric Wallace, Alvin Grissom II, Pedro Rodriguez, Mohit Iyyer, and Jordan Boyd-Graber. Pathologies of Neural Models Make Interpretation Difficult. Empirical Methods in Natural Language Processing, 2018. [Blog Post] [Bibtex]

@inproceedings{Feng:Wallace:II:Rodriguez:Iyyer:Boyd-Graber-2018,
	Author = {Shi Feng and Eric Wallace and Alvin Grissom II and Pedro Rodriguez and Mohit Iyyer and Jordan Boyd-Graber},
	Url = {docs/2018_emnlp_rs.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Location = {Brussels, Belgium},
	Year = {2018},
	Title = {Pathologies of Neural Models Make Interpretation Difficult},
}

Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, and Larry Davis. Learning to Color from Language. North American Association of Computational Linguistics, 2018. [Bibtex]

@inproceedings{Iyyer:Manjunatha:Boyd-Graber:Davis-2018,
	Author = {Mohit Iyyer and Varun Manjunatha and Jordan Boyd-Graber and Larry Davis},
	Url = {docs/2018_naacl_colorization.pdf},
	Booktitle = {North American Association of Computational Linguistics},
	Year = {2018},
	Title = {Learning to Color from Language},
}

Jordan Boyd-Graber, Shi Feng, and Pedro Rodriguez. Human-Computer Question Answering: The Case for Quizbowl. The NIPS '17 Competition: Building Intelligent Systems, 2018. [Bibtex]

@inbook{Boyd-Graber:Feng:Rodriguez-2018,
	Publisher = {Springer Verlag},
	Author = {Jordan Boyd-Graber and Shi Feng and Pedro Rodriguez},
	Url = {docs/2018_nips_qbcomp.pdf},
	Booktitle = {The NIPS '17 Competition: Building Intelligent Systems},
	Title = {Human-Computer Question Answering: The Case for Quizbowl},
	Year = {2018},
	Editor = {Sergio Escalera and Markus Weimer},
}

Closing the Loop

Alison Smith, Varun Kumar, Jordan Boyd-Graber, Kevin Seppi, and Leah Findlater. User-Centered Design and Evaluation of a Human-in-the-Loop Topic Modeling System. Intelligent User Interfaces, 2018. [Bibtex]

@inproceedings{Smith:Kumar:Boyd-Graber:Seppi:Findlater-2018,
	Author = {Alison Smith and Varun Kumar and Jordan Boyd-Graber and Kevin Seppi and Leah Findlater},
	Url = {docs/2018_iui_itm.pdf},
	Booktitle = {Intelligent User Interfaces},
	Year = {2018},
	Title = {User-Centered Design and Evaluation of a Human-in-the-Loop Topic Modeling System},
}

Alison won a best student paper honorable mention (3 out of 300)

Paul Felt, Eric Ringger, Kevin Seppi, and Jordan Boyd-Graber. Learning from Measurements in Crowdsourcing Models: Inferring Ground Truth from Diverse Annotation Types. International Conference on Computational Linguistics, 2018. [Bibtex]

@inproceedings{Felt:Ringger:Seppi:Boyd-Graber-2018,
	Author = {Paul Felt and Eric Ringger and Kevin Seppi and Jordan Boyd-Graber},
	Url = {docs/2018_coling_measurements.pdf},
	Booktitle = {International Conference on Computational Linguistics},
	Location = {Santa Fe, New Mexico},
	Year = {2018},
	Title = {Learning from Measurements in Crowdsourcing Models: Inferring Ground Truth from Diverse Annotation Types},
}

Jeff Lund, Connor Cook, Kevin Seppi, and Jordan Boyd-Graber. Tandem Anchoring: A Multiword Anchor Approach for Interactive Topic Modeling. Association for Computational Linguistics, 2017. [Code] [Bibtex]

@inproceedings{Lund:Cook:Seppi:Boyd-Graber-2017,
	Author = {Jeff Lund and Connor Cook and Kevin Seppi and Jordan Boyd-Graber},
	Url = {docs/2017_acl_multiword_anchors.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Vancouver, British Columbia},
	Year = {2017},
	Title = {Tandem Anchoring: A Multiword Anchor Approach for Interactive Topic Modeling},
}

Alison Smith, Varun Kumar, Jordan Boyd-Graber, Kevin Seppi, and Leah Findlater. Accounting for Input Uncertainty in Human-in-the-Loop Systems. CHI 2017 Designing for Uncertainty Workshop, 2017. [Bibtex]

@inproceedings{Smith:Kumar:Boyd-Graber:Seppi:Findlater-2017,
	Author = {Alison Smith and Varun Kumar and Jordan Boyd-Graber and Kevin Seppi and Leah Findlater},
	Url = {http://visualization.ischool.uw.edu/hci_uncertainty/papers/Paper11.pdf},
	Booktitle = {CHI 2017 Designing for Uncertainty Workshop},
	Year = {2017},
	Location = {Denver, CO},
	Title = {Accounting for Input Uncertainty in Human-in-the-Loop Systems},
}

You Lu, Jeff Lund, and Jordan Boyd-Graber. Why ADAGRAD Fails for Online Topic Modeling. Empirical Methods in Natural Language Processing, 2017. [Bibtex]

@inproceedings{Lu:Lund:Boyd-Graber-2017,
	Author = {You Lu and Jeff Lund and Jordan Boyd-Graber},
	Url = {docs/2017_emnlp_adagrad_olda.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Title = {Why ADAGRAD Fails for Online Topic Modeling},
	Year = {2017},
	Location = {Copenhagen, Denmark},
}

Tak Yeon Lee, Alison Smith, Kevin Seppi, Niklas Elmqvist, Jordan Boyd-Graber, and Leah Findlater. The Human Touch: How Non-expert Users Perceive, Interpret, and Fix Topic Models. International Journal of Human-Computer Studies, 2017. [Journal] [Bibtex]

@article{Lee:Smith:Seppi:Elmqvist:Boyd-Graber:Findlater-2017,
	Author = {Tak Yeon Lee and Alison Smith and Kevin Seppi and Niklas Elmqvist and Jordan Boyd-Graber and Leah Findlater},
	Url = {docs/2017_ijhcs_human_touch.pdf},
	Journal = {International Journal of Human-Computer Studies},
	Year = {2017},
	Title = {The Human Touch: How Non-expert Users Perceive, Interpret, and Fix Topic Models},
	Abstract = {Topic modeling is a common tool for understanding large bodies of text, but is typically provided as a “take it or leave it” proposition. Incorporating human knowledge in unsupervised learning is a promising approach to create high-quality topic models. Existing interactive systems and modeling algorithms support a wide range of refinement operations to express feedback. However, these systems’ interactions are primarily driven by algorithmic convenience, ignoring users who may lack expertise in topic modeling. To better understand how non-expert users understand, assess, and refine topics, we conduct two user studies—an in-person interview study and an online crowdsourced study. These studies demonstrate a disconnect between what non-expert users want and the complex, low-level operations that current interactive systems support. In particular, our findings include: (1) analysis of how non-expert users perceive topic models; (2) characterization of primary refinement operations expected by non-expert users and ordered by relative preference; (3) further evidence of the benefits of supporting users in directly refining a topic model; (4) design implications for future human-in-the-loop topic modeling interfaces.},
}

Jordan Boyd-Graber. Humans and Computers Working Together to Measure Machine Learning Interpretability. The Bridge, 2017. [Journal] [Bibtex]

@article{Boyd-Graber-2017,
	Volume = {47},
	Author = {Jordan Boyd-Graber},
	Journal = {The Bridge},
	Year = {2017},
	Title = {Humans and Computers Working Together to Measure Machine Learning Interpretability},
	Pages = {6--10},
}

Alison Smith, Tak Yeon Lee, Forough Poursabzi-Sangdeh, Jordan Boyd-Graber, Kevin Seppi, Niklas Elmqvist, and Leah Findlater. Evaluating Visual Representations for Topic Understanding and Their Effects on Manually Generated Labels. Transactions of the Association for Computational Linguistics, 2017. [Journal] [Data] [Bibtex]

@article{Smith:Lee:Poursabzi-Sangdeh:Boyd-Graber:Seppi:Elmqvist:Findlater-2017,
	Volume = {5},
	Author = {Alison Smith and Tak Yeon Lee and Forough Poursabzi-Sangdeh and Jordan Boyd-Graber and Kevin Seppi and Niklas Elmqvist and Leah Findlater},
	Url = {docs/2017_tacl_eval_tm_viz.pdf},
	Journal = {Transactions of the Association for Computational Linguistics},
	Year = {2017},
	Pages = {1--15},
	Title = {Evaluating Visual Representations for Topic Understanding and Their Effects on Manually Generated Labels},
	Abstract = {Probabilistic topic models are important tools for indexing, summarizing, and analyzing large document collections by their themes.  However, promoting end-user understanding of topics remains an open research problem.  We compare labels generated by users given four topic visualization techniques—word lists, word lists with bars, word clouds, and network graphs—against each other and against automatically generated labels.  Our basis of comparison is participant ratings of how well labels describe documents from the topic. Our study has two phases: a labeling phase where participants label visualized topics and a validation phase where different participants select which labels best describe the topics' documents.  Although all visualizations produce similar quality labels, simple visualizations such as word lists allow participants to quickly understand topics, while complex visualizations take longer but expose multi-word expressions that simpler visualizations obscure.  Automatic labels lag behind user-created labels, but our dataset of manually labeled topics highlights linguistic patterns (e.g., hypernyms, phrases) that can be used to improve automatic topic labeling algorithms.},
}

Forough Poursabzi-Sangdeh, Jordan Boyd-Graber, Leah Findlater, and Kevin Seppi. ALTO: Active Learning with Topic Overviews for Speeding Label Induction and Document Labeling. Association for Computational Linguistics, 2016. [Code] [Bibtex]

@inproceedings{Poursabzi-Sangdeh:Boyd-Graber:Findlater:Seppi-2016,
	Author = {Forough Poursabzi-Sangdeh and Jordan Boyd-Graber and Leah Findlater and Kevin Seppi},
	Url = {docs/2016_acl_doclabel.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Berlin, Brandenburg},
	Year = {2016},
	Title = {ALTO: Active Learning with Topic Overviews for Speeding Label Induction and Document Labeling},
}

Alison Smith, Tak Yeon Lee, Forough Poursabzi-Sangdeh, Jordan Boyd-Graber, Kevin Seppi, Niklas Elmqvist, and Leah Findlater. Human-Centered and Interactive: Expanding the Impact of Topic Models. CHI Human Centred Machine Learning Workshop, 2016. [Bibtex]

@inproceedings{Smith:Lee:Poursabzi-Sangdeh:Boyd-Graber:Seppi:Elmqvist:Findlater-2016,
	Author = {Alison Smith and Tak Yeon Lee and Forough Poursabzi-Sangdeh and Jordan Boyd-Graber and Kevin Seppi and Niklas Elmqvist and Leah Findlater},
	Booktitle = {CHI Human Centred Machine Learning Workshop},
	Year = {2016},
	Location = {San Jose, CA},
	Title = {Human-Centered and Interactive: Expanding the Impact of Topic Models},
}

Md Arafat Sultan, Jordan Boyd-Graber, and Tamara Sumner. Bayesian Supervised Domain Adaptation for Short Text Similarity. North American Association for Computational Linguistics, 2016. [Talk] [Bibtex]

@inproceedings{Sultan:Boyd-Graber:Sumner-2016,
	Author = {Md Arafat Sultan and Jordan Boyd-Graber and Tamara Sumner},
	Url = {docs/2016_naacl_sts.pdf},
	Booktitle = {North American Association for Computational Linguistics},
	Location = {San Diego, CA},
	Year = {2016},
	Title = {Bayesian Supervised Domain Adaptation for Short Text Similarity},
}

Viet-An Nguyen, Jordan Boyd-Graber, Philip Resnik, and Kristina Miler. Tea Party in the House: A Hierarchical Ideal Point Topic Model and Its Application to Republican Legislators in the 112th Congress. Association for Computational Linguistics, 2015. [Talk] [Code] [LaTeX] [Bibtex]

@inproceedings{Nguyen:Boyd-Graber:Resnik:Miler-2015,
	Author = {Viet-An Nguyen and Jordan Boyd-Graber and Philip Resnik and Kristina Miler},
	Url = {docs/2015_acl_teaparty.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Beijing, China},
	Year = {2015},
	Title = {Tea Party in the House: A Hierarchical Ideal Point Topic Model and Its Application to Republican Legislators in the 112th Congress},
}

Paul Felt, Eric Ringger, Jordan Boyd-Graber, and Kevin Seppi. Making the Most of Crowdsourced Document Annotations: Confused Supervised LDA. Conference on Computational Natural Language Learning, 2015. [Talk] [Bibtex]

@inproceedings{Felt:Ringger:Boyd-Graber:Seppi-2015,
	Author = {Paul Felt and Eric Ringger and Jordan Boyd-Graber and Kevin Seppi},
	Url = {docs/2015_conll_cslda.pdf},
	Booktitle = {Conference on Computational Natural Language Learning},
	Location = {Beijing, China},
	Year = {2015},
	Title = {Making the Most of Crowdsourced Document Annotations: Confused Supervised {LDA}},
}

This paper received the best paper award at CoNLL

Yi Yang, Doug Downey, and Jordan Boyd-Graber. Efficient Methods for Incorporating Knowledge into Topic Models. Empirical Methods in Natural Language Processing, 2015. [Code] [Bibtex]

@inproceedings{Yang:Downey:Boyd-Graber-2015,
	Author = {Yi Yang and Doug Downey and Jordan Boyd-Graber},
	Url = {docs/2015_emnlp_fast_priors.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Location = {Lisbon, Portugal},
	Year = {2015},
	Title = {Efficient Methods for Incorporating Knowledge into Topic Models},
}

Stephen H. Bach, Bert Huang, Jordan Boyd-Graber, and Lise Getoor. Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs. International Conference on Machine Learning, 2015. [Video] [Bibtex]

@inproceedings{Bach:Huang:Boyd-Graber:Getoor-2015,
	Author = {Stephen H. Bach and Bert Huang and Jordan Boyd-Graber and Lise Getoor},
	Url = {docs/2015_icml_paired_dual.pdf},
	Booktitle = {International Conference on Machine Learning},
	Title = {Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs},
	Year = {2015},
	Location = {Lille, France},
}

Thang Nguyen, Jordan Boyd-Graber, Jeff Lund, Kevin Seppi, and Eric Ringger. Is your anchor going up or down? Fast and accurate supervised topic models. North American Association for Computational Linguistics, 2015. [Bibtex]

@inproceedings{Nguyen:Boyd-Graber:Lund:Seppi:Ringger-2015,
	Author = {Thang Nguyen and Jordan Boyd-Graber and Jeff Lund and Kevin Seppi and Eric Ringger},
	Url = {docs/2015_naacl_supervised_anchor.pdf},
	Booktitle = {North American Association for Computational Linguistics},
	Location = {Denver, Colorado},
	Year = {2015},
	Title = {Is your anchor going up or down?  {F}ast and accurate supervised topic models},
}

Alison Smith, Jason Chuang, Yuening Hu, Jordan Boyd-Graber, and Leah Findlater. Concurrent Visualization of Relationships between Words and Topics in Topic Models. ACL Workshop on Workshop on Interactive Language Learning, Visualization, and Interfaces, 2014. [Bibtex]

@inproceedings{Smith:Chuang:Hu:Boyd-Graber:Findlater-2014,
	Author = {Alison Smith and Jason Chuang and Yuening Hu and Jordan Boyd-Graber and Leah Findlater},
	Booktitle = {ACL Workshop on Workshop on Interactive Language Learning, Visualization, and Interfaces},
	Location = {Baltimore, Maryland},
	Year = {2014},
	Title = {Concurrent Visualization of Relationships between Words and Topics in Topic Models},
}

Yuening Hu, Jordan Boyd-Graber, Brianna Satinoff, and Alison Smith. Interactive Topic Modeling. Machine Learning, 2014. [Journal] [Frontend Code] [Backend Code] [Bibtex]

@article{Hu:Boyd-Graber:Satinoff:Smith-2014,
	Publisher = {Springer},
	Author = {Yuening Hu and Jordan Boyd-Graber and Brianna Satinoff and Alison Smith},
	Url = {docs/2014_mlj_itm.pdf},
	Journal = {Machine Learning},
	Title = {Interactive Topic Modeling},
	Volume = {95},
	Year = {2014},
	Pages = {423--469},
}

Yuening Hu, Jordan Boyd-Graber, and Brianna Satinoff. Interactive Topic Modeling. Association for Computational Linguistics, 2011. [Slides] [Code] [Bibtex]

@inproceedings{Hu:Boyd-Graber:Satinoff-2011,
	Author = {Yuening Hu and Jordan Boyd-Graber and Brianna Satinoff},
	Url = {docs/itm.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Portland, Oregon},
	Year = {2011},
	Title = {Interactive Topic Modeling},
}

Cross-Language Bayesian Models for Web-Scale Text Analysis

Thang Nguyen, Yuening Hu, and Jordan Boyd-Graber. Anchors Regularized: Adding Robustness and Extensibility to Scalable Topic-Modeling Algorithms. Association for Computational Linguistics, 2014. [Talk] [Bibtex]

@inproceedings{Nguyen:Hu:Boyd-Graber-2014,
	Author = {Thang Nguyen and Yuening Hu and Jordan Boyd-Graber},
	Url = {docs/2014_acl_anchor_reg.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Baltimore, MD},
	Year = {2014},
	Title = {Anchors Regularized: Adding Robustness and Extensibility to Scalable Topic-Modeling Algorithms},
}

Mohit Iyyer, Peter Enns, Jordan Boyd-Graber, and Philip Resnik. Political Ideology Detection Using Recursive Neural Networks. Association for Computational Linguistics, 2014. [Data] [Bibtex]

@inproceedings{Iyyer:Enns:Boyd-Graber:Resnik-2014,
	Author = {Mohit Iyyer and Peter Enns and Jordan Boyd-Graber and Philip Resnik},
	Url = {docs/2014_acl_rnn_ideology.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Baltimore, MD},
	Year = {2014},
	Title = {Political Ideology Detection Using Recursive Neural Networks},
}

Yuening Hu, Jordan Boyd-Graber, Brianna Satinoff, and Alison Smith. Interactive Topic Modeling. Machine Learning, 2014. [Journal] [Frontend Code] [Backend Code] [Bibtex]

@article{Hu:Boyd-Graber:Satinoff:Smith-2014,
	Publisher = {Springer},
	Author = {Yuening Hu and Jordan Boyd-Graber and Brianna Satinoff and Alison Smith},
	Url = {docs/2014_mlj_itm.pdf},
	Journal = {Machine Learning},
	Title = {Interactive Topic Modeling},
	Volume = {95},
	Year = {2014},
	Pages = {423--469},
}

Viet-An Nguyen, Jordan Boyd-Graber, Philip Resnik, Deborah Cai, Jennifer Midberry, and Yuanxin Wang. Modeling Topic Control to Detect Influence in Conversations using Nonparametric Topic Models. Machine Learning, 2014. [Journal] [Code] [Data] [Bibtex]

@article{Nguyen:Boyd-Graber:Resnik:Cai:Midberry:Wang-2014,
	Publisher = {Springer},
	Author = {Viet-An Nguyen and Jordan Boyd-Graber and Philip Resnik and Deborah Cai and Jennifer Midberry and Yuanxin Wang},
	Url = {docs/2014_mlj_influencer.pdf},
	Journal = {Machine Learning},
	Title = {Modeling Topic Control to Detect Influence in Conversations using Nonparametric Topic Models},
	Volume = {95},
	Year = {2014},
	Pages = {381--421},
}

Ke Zhai, Jordan Boyd-Graber, and Shay B. Cohen. Hybrid Online Inference with Adaptor Grammars. NIPS Workshop on Advances in Variational Inference, 2014. [Bibtex]

@article{Zhai:Boyd-Graber:Cohen-2014,
	Author = {Ke Zhai and Jordan Boyd-Graber and Shay B. Cohen},
	Booktitle = {NIPS Workshop on Advances in Variational Inference},
	Year = {2014},
	Title = {Hybrid Online Inference with Adaptor Grammars},
}

Ke Zhai, Jordan Boyd-Graber, and Shay B. Cohen. Online Adaptor Grammars with Hybrid Inference. Transactions of the Association for Computational Linguistics, 2014. [Code] [Bibtex]

@article{Zhai:Boyd-Graber:Cohen-2014,
	Publisher = {Association for Computational Linguistics},
	Author = {Ke Zhai and Jordan Boyd-Graber and Shay B. Cohen},
	Url = {docs/2014_tacl_ag_vb_online.pdf},
	Journal = {Transactions of the Association for Computational Linguistics},
	Year = {2014},
	Title = {Online Adaptor Grammars with Hybrid Inference},
}

Jordan Boyd-Graber, Kimberly Glasgow, and Jackie Sauter Zajac. Spoiler Alert: Machine Learning Approaches to Detect Social Media Posts with Revelatory Information. ASIST 2013: The 76th Annual Meeting of the American Society for Information Science and Technology, 2013. [Data] [Bibtex]

@inproceedings{Boyd-Graber:Glasgow:Zajac-2013,
	Author = {Jordan Boyd-Graber and Kimberly Glasgow and Jackie Sauter Zajac},
	Url = {docs/2013_spoiler.pdf},
	Booktitle = {ASIST 2013: The 76th Annual Meeting of the American Society for Information Science and Technology},
	Location = {Montreal, Canada},
	Year = {2013},
	Title = {Spoiler Alert: Machine Learning Approaches to Detect Social Media Posts with Revelatory Information},
}

Ke Zhai and Jordan Boyd-Graber. Online Topic Models with Infinite Vocabulary. International Conference on Machine Learning, 2013. [Poster] [Talk] [Code] [Bibtex]

@inproceedings{Zhai:Boyd-Graber-2013,
	Author = {Ke Zhai and Jordan Boyd-Graber},
	Url = {docs/2013_icml_infvoc.pdf},
	Booktitle = {International Conference on Machine Learning},
	Year = {2013},
	Title = {Online Topic Models with Infinite Vocabulary},
}

Viet-An Nguyen, Jordan Boyd-Graber, and Stephen Altschul. Dirichlet Mixtures, the Dirichlet Process, and the Structure of Protein Space. Journal of Computational Biology, 2013. [Journal] [Bibtex]

@article{Nguyen:Boyd-Graber:Altschul-2013,
	Author = {Viet-An Nguyen and Jordan Boyd-Graber and Stephen Altschul},
	Url = {docs/2013_dp_protein.pdf},
	Journal = {Journal of Computational Biology},
	Number = {1},
	Volume = {20},
	Year = {2013},
	Title = {Dirichlet Mixtures, the Dirichlet Process, and the Structure of Protein Space},
}

Yuening Hu, Jordan Boyd-Graber, Hal Daumé III, and Z. Irene Ying. Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent. Neural Information Processing Systems, 2013. [Supplement] [Data] [Bibtex]

@inproceedings{Hu:Boyd-Graber:Daume-III:Ying-2013,
	Author = {Yuening Hu and Jordan Boyd-Graber and Hal {Daum\'{e} III} and Z. Irene Ying},
	Url = {docs/2013_coalescent.pdf},
	Booktitle = {Neural Information Processing Systems},
	Title = {Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent},
	Year = {2013},
}

Viet-An Nguyen, Jordan Boyd-Graber, and Philip Resnik. Lexical and Hierarchical Topic Regression. Neural Information Processing Systems, 2013. [Supplement] [Bibtex]

@inproceedings{Nguyen:Boyd-Graber:Resnik-2013,
	Author = {Viet-An Nguyen and Jordan Boyd-Graber and Philip Resnik},
	Url = {docs/2013_shlda.pdf},
	Booktitle = {Neural Information Processing Systems},
	Title = {Lexical and Hierarchical Topic Regression},
	Year = {2013},
	Location = {Lake Tahoe, Nevada},
}

Viet-An Nguyen, Yuening Hu, Jordan Boyd-Graber, and Philip Resnik. Argviz: Interactive Visualization of Topic Dynamics in Multi-party Conversations. North American Association for Computational Linguistics, 2013. [Bibtex]

@inproceedings{Nguyen:Hu:Boyd-Graber:Resnik-2013,
	Author = {Viet-An Nguyen and Yuening Hu and Jordan Boyd-Graber and Philip Resnik},
	Url = {docs/2013_argviz.pdf},
	Booktitle = {North American Association for Computational Linguistics},
	Location = {Atlanta Georgia},
	Year = {2013},
	Title = {Argviz: Interactive Visualization of Topic Dynamics in Multi-party Conversations},
}

Naho Orita, Rebecca McKeown, Naomi H. Feldman, Jeffrey Lidz, and Jordan Boyd-Graber. Discovering Pronoun Categories using Discourse Information. Proceedings of the Cognitive Science Society, 2013. [Bibtex]

@inproceedings{Orita:McKeown:Feldman:Lidz:Boyd-Graber-2013,
	Author = {Naho Orita and Rebecca McKeown and Naomi H. Feldman and Jeffrey Lidz and Jordan Boyd-Graber},
	Url = {docs/2013_cogsci_pronoun.pdf},
	Booktitle = {Proceedings of the Cognitive Science Society},
	Location = {Berlin, Germany},
	Year = {2013},
	Title = {Discovering Pronoun Categories using Discourse Information},
}

Ke Zhai, Jordan Boyd-Graber, Nima Asadi, and Mohamad Alkhouja. Mr. LDA: A Flexible Large Scale Topic Modeling Package using Variational Inference in MapReduce. ACM International Conference on World Wide Web, 2012. [Code] [Slides] [Bibtex]

@inproceedings{Zhai:Boyd-Graber:Asadi:Alkhouja-2012,
	Author = {Ke Zhai and Jordan Boyd-Graber and Nima Asadi and Mohamad Alkhouja},
	Url = {docs/mrlda.pdf},
	Booktitle = {ACM International Conference on World Wide Web},
	Title = {{Mr. LDA}: A Flexible Large Scale Topic Modeling Package using Variational Inference in MapReduce},
	Year = {2012},
	Location = {Lyon, France},
}

Yuening Hu and Jordan Boyd-Graber. Efficient Tree-Based Topic Modeling. Association for Computational Linguistics, 2012. [Bibtex]

@inproceedings{Hu:Boyd-Graber-2012,
	Author = {Yuening Hu and Jordan Boyd-Graber},
	Url = {docs/acl_2012_fttm.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Jeju, South Korea},
	Year = {2012},
	Title = {Efficient Tree-Based Topic Modeling},
}

Vladimir Eidelman, Jordan Boyd-Graber, and Philip Resnik. Topic Models for Dynamic Translation Model Adaptation. Association for Computational Linguistics, 2012. [Presentation] [More Recent Paper] [Bibtex]
```
@inproceedings{Eidelman:Boyd-Graber:Resnik-2012,
	Author = {Vladimir Eidelman and Jordan Boyd-Graber and Philip Resnik},
	Url = {docs/acl_2012_tm_for_mt.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Jeju, South Korea},
	Year = {2012},
	Title = {Topic Models for Dynamic Translation Model Adaptation},
}
```
For a more thorough evaluation and an exploration of more advanced topic models for machine translation, see: Yuening Hu, Ke Zhai, Vlad Eidelman, and Jordan Boyd-Graber. Polylingual Tree-Based Topic Models for Translation Domain Adaptation. Association for Computational Linguistics, 2014.

Viet-An Nguyen, Jordan Boyd-Graber, and Philip Resnik. SITS: A Hierarchical Nonparametric Model using Speaker Identity for Topic Segmentation in Multiparty Conversations. Association for Computational Linguistics, 2012. [Data] [Code] [Slides] [Appendix] [Bibtex]

@inproceedings{Nguyen:Boyd-Graber:Resnik-2012,
	Author = {Viet-An Nguyen and Jordan Boyd-Graber and Philip Resnik},
	Url = {docs/acl_2012_sits.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Jeju, South Korea},
	Year = {2012},
	Title = {{SITS}: A Hierarchical Nonparametric Model using Speaker Identity for Topic Segmentation in Multiparty Conversations},
}

Yuening Hu, Ke Zhai, Sinead Williamson, and Jordan Boyd-Graber. Modeling Images using Transformed Indian Buffet Processes. International Conference of Machine Learning, 2012. [Code] [Data] [Presentation] [Bibtex]

@inproceedings{Hu:Zhai:Williamson:Boyd-Graber-2012,
	Author = {Yuening Hu and Ke Zhai and Sinead Williamson and Jordan Boyd-Graber},
	Url = {docs/mtibp_icml_2012.pdf},
	Booktitle = {International Conference of Machine Learning},
	Location = {Edinburgh, Scotland},
	Year = {2012},
	Title = {Modeling Images using Transformed {I}ndian Buffet Processes},
}

LORELEI

Shi Feng and Jordan Boyd-Graber. What AI can do for me: Evaluating Machine Learning Interpretations in Cooperative Play. Intelligent User Interfaces, 2019. [Bibtex]

@inproceedings{Feng:Boyd-Graber-2019,
	Author = {Shi Feng and Jordan Boyd-Graber},
	Url = {docs/2019_iui_augment.pdf},
	Booktitle = {Intelligent User Interfaces},
	Location = {Los Angeles, CA},
	Year = {2019},
	Title = {What AI can do for me: Evaluating Machine Learning Interpretations in Cooperative Play},
}

@inproceedings{Feng:Wallace:II:Rodriguez:Iyyer:Boyd-Graber-2018,
	Author = {Shi Feng and Eric Wallace and Alvin Grissom II and Pedro Rodriguez and Mohit Iyyer and Jordan Boyd-Graber},
	Url = {docs/2018_emnlp_rs.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Location = {Brussels, Belgium},
	Year = {2018},
	Title = {Pathologies of Neural Models Make Interpretation Difficult},
}

Michelle Yuan, Benjamin Van Durme, and Jordan Boyd-Graber. Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages. Neural Information Processing Systems, 2018. [Code] [Bibtex]

@inproceedings{Yuan:Van-Durme:Boyd-Graber-2018,
	Author = {Michelle Yuan and Benjamin {Van Durme} and Jordan Boyd-Graber},
	Url = {docs/2018_neurips_mtanchor.pdf},
	Booktitle = {Neural Information Processing Systems},
	Location = {Montreal, Quebec},
	Year = {2018},
	Title = {Multilingual Anchoring: Interactive Topic Modeling and Alignment  Across Languages},
}

Shudong Hao, Michael J. Paul, and Jordan Boyd-Graber. Lessons from the Bible on Modern Topics: Multilingual Topic Model Evaluation on Low-Resource Languages. North American Association for Computational Linguistics, 2018. [Bibtex]

@inproceedings{Hao:Paul:Boyd-Graber-2018,
	Author = {Shudong Hao and Michael J. Paul and Jordan Boyd-Graber},
	Url = {docs/2018_naacl_mltm_eval.pdf},
	Booktitle = {North American Association for Computational Linguistics},
	Location = {New Orleans, LA},
	Year = {2018},
	Title = {Lessons from the Bible on Modern Topics: Multilingual Topic Model Evaluation on Low-Resource Languages},
}

Weiwei Yang, Jordan Boyd-Graber, and Philip Resnik. Adapting Topic Models using Lexical Associations with Tree Priors. Empirical Methods in Natural Language Processing, 2017. [Bibtex]

@inproceedings{Yang:Boyd-Graber:Resnik-2017,
	Author = {Weiwei Yang and Jordan Boyd-Graber and Philip Resnik},
	Url = {docs/2017_emnlp_tree_prior.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Title = {Adapting Topic Models using Lexical Associations with Tree Priors},
	Year = {2017},
	Location = {Copenhagen, Denmark},
}

Weiwei Yang, Jordan Boyd-Graber, and Philip Resnik. A Discriminative Topic Model using Document Network Structure. Association for Computational Linguistics, 2016. [Supplement] [Bibtex]

@inproceedings{Yang:Boyd-Graber:Resnik-2016,
	Author = {Weiwei Yang and Jordan Boyd-Graber and Philip Resnik},
	Url = {docs/2016_acl_docblock.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Berlin, Brandenburg},
	Year = {2016},
	Title = {A Discriminative Topic Model using Document Network Structure},
}

Weiwei Yang, Jordan Boyd-Graber, and Philip Resnik. Birds of a Feather in the Same Nest: A Discriminative Topic Model using Block-based Priors. Mid-Atlantic Student Colloquium on Speech, Language, and Learning, 2016. [Bibtex]

@inproceedings{Yang:Boyd-Graber:Resnik-2016,
	Author = {Weiwei Yang and Jordan Boyd-Graber and Philip Resnik},
	Booktitle = {Mid-Atlantic Student Colloquium on Speech, Language, and Learning},
	Location = {Philadephia},
	Year = {2016},
	Title = {Birds of a Feather in the Same Nest: A Discriminative Topic Model using Block-based Priors},
}

Weiwei Yang, Jordan Boyd-Graber, and Philip Resnik. Birds of a Feather Linked Together: A Discriminative Topic Model using Link-based Priors. Empirical Methods in Natural Language Processing, 2015. [Bibtex]

@inproceedings{Yang:Boyd-Graber:Resnik-2015,
	Author = {Weiwei Yang and Jordan Boyd-Graber and Philip Resnik},
	Url = {docs/2015_emnlp_hinge_link.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Title = {Birds of a Feather Linked Together: A Discriminative Topic Model using Link-based Priors},
	Year = {2015},
	Location = {Lisbon, Portugal},
}

Scaling Insight

Aaron Gerow, Yuening Hu, Jordan Boyd-Graber, David M. Blei, and James A. Evans. Measuring Discursive Influence Across Scholarship. Proceedings of the National Academies of Science, 2018. [Journal] [Bibtex]

@article{Gerow:Hu:Boyd-Graber:Blei:Evans-2018,
	Author = {Aaron Gerow and Yuening Hu and Jordan Boyd-Graber and David M. Blei and James A. Evans},
	Journal = {Proceedings of the National Academies of Science},
	Year = {2018},
	Title = {Measuring Discursive Influence Across Scholarship},
}

You Lu, Jeff Lund, and Jordan Boyd-Graber. Why ADAGRAD Fails for Online Topic Modeling. Empirical Methods in Natural Language Processing, 2017. [Bibtex]

@inproceedings{Lu:Lund:Boyd-Graber-2017,
	Author = {You Lu and Jeff Lund and Jordan Boyd-Graber},
	Url = {docs/2017_emnlp_adagrad_olda.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Title = {Why ADAGRAD Fails for Online Topic Modeling},
	Year = {2017},
	Location = {Copenhagen, Denmark},
}

@inproceedings{Poursabzi-Sangdeh:Boyd-Graber:Findlater:Seppi-2016,
	Author = {Forough Poursabzi-Sangdeh and Jordan Boyd-Graber and Leah Findlater and Kevin Seppi},
	Url = {docs/2016_acl_doclabel.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Berlin, Brandenburg},
	Year = {2016},
	Title = {ALTO: Active Learning with Topic Overviews for Speeding Label Induction and Document Labeling},
}

Evgeny Klochikhin and Jordan Boyd-Graber. Text Analysis. Big Data and Social Science Research: Theory and Practical Approaches, 2016. [Bibtex]

@inbook{Klochikhin:Boyd-Graber-2016,
	Publisher = {Taylor Francis},
	Author = {Evgeny Klochikhin and Jordan Boyd-Graber},
	Booktitle = {Big Data and Social Science Research: Theory and Practical Approaches},
	Title = {Text Analysis},
	Year = {2016},
	Editor = {Julia Lane and Ian Foster and Rayid Ghani and Ron Jarmin and Frauke Kreuter},
}

Forough Poursabzi-Sangdeh and Jordan Boyd-Graber. Speeding Document Annotation with Topic Models. NAACL Student Research Workshop, 2015. [Bibtex]

@inproceedings{Poursabzi-Sangdeh:Boyd-Graber-2015,
	Author = {Forough Poursabzi-Sangdeh and Jordan Boyd-Graber},
	Booktitle = {NAACL Student Research Workshop},
	Location = {Denver, CO},
	Year = {2015},
	Title = {Speeding Document Annotation with Topic Models},
}

Thinking on Your Feet

Mohit Iyyer, Varun Manjunatha, Anupam Guha, Yogarshi Vyas, Jordan Boyd-Graber, Hal Daumé III, and Larry Davis. The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives. Computer Vision and Pattern Recognition, 2017. [Code/Data] [Bibtex]

@inproceedings{Iyyer:Manjunatha:Guha:Vyas:Boyd-Graber:Daume-III:Davis-2017,
	Author = {Mohit Iyyer and Varun Manjunatha and Anupam Guha and Yogarshi Vyas and Jordan Boyd-Graber and Hal {Daum\'{e} III} and Larry Davis},
	Url = {docs/2017_cvpr_comics.pdf},
	Booktitle = {Computer Vision and Pattern Recognition},
	Year = {2017},
	Title = {The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives},
}

Khanh Nguyen, Jordan Boyd-Graber, and Hal Daumé III. Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback. Empirical Methods in Natural Language Processing, 2017. [Code] [Bibtex]

@inproceedings{Nguyen:Boyd-Graber:Daume-III-2017,
	Author = {Khanh Nguyen and Jordan Boyd-Graber and Hal {Daum\'{e} III}},
	Url = {docs/2017_emnlp_bandit_mt.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Location = {Copenhagen, Denmark},
	Year = {2017},
	Title = {Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback},
}

Alvin Grissom II, Naho Orita, and Jordan Boyd-Graber. Incremental Prediction of Sentence-final Verbs. Conference on Computational Natural Language Learning, 2016. [Bibtex]

@inproceedings{Grissom-II:Orita:Boyd-Graber-2016,
	Author = {Alvin {Grissom II} and Naho Orita and Jordan Boyd-Graber},
	Url = {docs/2016_conll_verbpred.pdf},
	Booktitle = {Conference on Computational Natural Language Learning},
	Location = {Berlin, Germany},
	Year = {2016},
	Title = {Incremental Prediction of Sentence-final Verbs},
}

He He, Jordan Boyd-Graber, Kevin Kwok, and Hal Daumé III. Opponent Modeling in Deep Reinforcement Learning. International Conference on Machine Learning, 2016. [Video] [Bibtex]

@inproceedings{He:Boyd-Graber:Kwok:Daume-III-2016,
	Author = {He He and Jordan Boyd-Graber and Kevin Kwok and Hal {Daum\'{e} III}},
	Url = {docs/2016_icml_opponent.pdf},
	Booktitle = {International Conference on Machine Learning},
	Location = {New York, NY},
	Year = {2016},
	Title = {Opponent Modeling in Deep Reinforcement Learning},
}

Anupam Guha, Mohit Iyyer, and Jordan Boyd-Graber. A Distorted Skull Lies in the Bottom Center: Identifying Paintings from Text Descriptions. NAACL Human-Computer Question Answering Workshop, 2016. [Data] [Bibtex]

@inproceedings{Guha:Iyyer:Boyd-Graber-2016,
	Author = {Anupam Guha and Mohit Iyyer and Jordan Boyd-Graber},
	Url = {docs/2016_naacl_paintings.pdf},
	Booktitle = {NAACL Human-Computer Question Answering Workshop},
	Location = {San Diego, CA},
	Year = {2016},
	Title = {A Distorted Skull Lies in the Bottom Center: Identifying Paintings from Text Descriptions},
}

Mohit Iyyer, Anupam Guha, Snigdha Chaturvedi, Jordan Boyd-Graber, and Hal Daumé III. Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships. North American Association for Computational Linguistics, 2016. [Code/Data] [Bibtex]

@inproceedings{Iyyer:Guha:Chaturvedi:Boyd-Graber:Daume-III-2016,
	Author = {Mohit Iyyer and Anupam Guha and Snigdha Chaturvedi and Jordan Boyd-Graber and Hal {Daum\'{e} III}},
	Url = {docs/2016_naacl_relationships.pdf},
	Booktitle = {North American Association for Computational Linguistics},
	Location = {San Diego, CA},
	Year = {2016},
	Title = {Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships},
}

Best paper award (2 out of 1592)

He He, Jordan Boyd-Graber, and Hal Daumé III. Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation. North American Association for Computational Linguistics, 2016. [Talk] [Bibtex]

@inproceedings{He:Boyd-Graber:Daume-III-2016,
	Author = {He He and Jordan Boyd-Graber and Hal {Daum\'{e} III}},
	Url = {docs/2016_naacl_interpretese.pdf},
	Booktitle = {North American Association for Computational Linguistics},
	Location = {San Diego, CA},
	Year = {2016},
	Title = {Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation},
}

Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, and Hal Daumé III. Deep Unordered Composition Rivals Syntactic Methods for Text Classification. Association for Computational Linguistics, 2015. [Slides] [Code] [Talk] [Bibtex]

@inproceedings{Iyyer:Manjunatha:Boyd-Graber:Daume-III-2015,
	Author = {Mohit Iyyer and Varun Manjunatha and Jordan Boyd-Graber and Hal {Daum\'{e} III}},
	Url = {docs/2015_acl_dan.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Beijing, China},
	Year = {2015},
	Title = {Deep Unordered Composition Rivals Syntactic Methods for Text Classification},
}

Vlad Niculae, Srijan Kumar, Jordan Boyd-Graber, and Cristian Danescu-Niculescu-Mizil. Linguistic Harbingers of Betrayal: A Case Study on an Online Strategy Game. Association for Computational Linguistics, 2015. [Code/Data] [Bibtex]

@inproceedings{Niculae:Kumar:Boyd-Graber:Danescu-Niculescu-Mizil-2015,
	Author = {Vlad Niculae and Srijan Kumar and Jordan Boyd-Graber and Cristian Danescu-Niculescu-Mizil},
	Url = {docs/2015_acl_diplomacy.pdf},
	Booktitle = {Association for Computational Linguistics},
	Location = {Beijing, China},
	Year = {2015},
	Title = {Linguistic Harbingers of Betrayal: A Case Study on an Online Strategy Game},
}

He He, Alvin Grissom II, Jordan Boyd-Graber, and Hal Daumé III. Syntax-based Rewriting for Simultaneous Machine Translation. Empirical Methods in Natural Language Processing, 2015. [Bibtex]

@inproceedings{He:Grissom-II:Boyd-Graber:Daume-III-2015,
	Author = {He He and Alvin {Grissom II} and Jordan Boyd-Graber and Hal {Daum\'{e} III}},
	Url = {docs/2015_emnlp_rewrite.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Location = {Lisbon, Portugal},
	Year = {2015},
	Title = {Syntax-based Rewriting for Simultaneous Machine Translation},
}

Jordan Boyd-Graber, Mohit Iyyer, He He, and Hal Daumé III. Interactive Incremental Question Answering. Neural Information Processing Systems, 2015. [Bibtex]

@inproceedings{Boyd-Graber:Iyyer:He:Daume-III-2015,
	Author = {Jordan Boyd-Graber and Mohit Iyyer and He He and Hal {Daum\'{e} III}},
	Booktitle = {Neural Information Processing Systems},
	Location = {Montreal, Canada},
	Year = {2015},
	Title = {Interactive Incremental Question Answering},
}

This won the best demonstration award at NIPS 2015

Anupam Guha, Mohit Iyyer, Danny Bouman, and Jordan Boyd-Graber. Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers. North American Association for Computational Linguistics, 2015. [Code/Data] [Slides] [Video] [LaTeX] [Bibtex]

@inproceedings{Guha:Iyyer:Bouman:Boyd-Graber-2015,
	Author = {Anupam Guha and Mohit Iyyer and Danny Bouman and Jordan Boyd-Graber},
	Url = {docs/2015_naacl_qb_coref.pdf},
	Booktitle = {North American Association for Computational Linguistics},
	Location = {Denver, Colorado},
	Year = {2015},
	Title = {Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers},
}

Mohit Iyyer, Jordan Boyd-Graber, Leonardo Claudino, Richard Socher, and Hal Daumé III. A Neural Network for Factoid Question Answering over Paragraphs. Empirical Methods in Natural Language Processing, 2014. [Code/Data] [Bibtex]

@inproceedings{Iyyer:Boyd-Graber:Claudino:Socher:Daume-III-2014,
	Author = {Mohit Iyyer and Jordan Boyd-Graber and Leonardo Claudino and Richard Socher and Hal {Daum\'{e} III}},
	Url = {docs/2014_emnlp_qb_rnn.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Location = {Doha, Qatar},
	Year = {2014},
	Title = {A Neural Network for Factoid Question Answering over Paragraphs},
}

The partial derivatives of "C" and "J" with respect to the parameters should be switched in Equation 7.

Alvin Grissom II, He He, Jordan Boyd-Graber, John Morgan, and Hal Daumé III. Don't Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation. Empirical Methods in Natural Language Processing, 2014. [Talk] [Bibtex]

@inproceedings{Grissom-II:He:Boyd-Graber:Morgan:Daume-III-2014,
	Author = {Alvin {Grissom II} and He He and Jordan Boyd-Graber and John Morgan and Hal {Daum\'{e} III}},
	Url = {docs/2014_emnlp_simtrans.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Location = {Doha, Qatar},
	Year = {2014},
	Title = {Don't Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation},
}

Mohit Iyyer, Jordan Boyd-Graber, and Hal Daumé III. Generating Sentences from Semantic Vector Space Representations. NIPS Workshop on Learning Semantics, 2014. [Bibtex]

@inproceedings{Iyyer:Boyd-Graber:Daume-III-2014,
	Author = {Mohit Iyyer and Jordan Boyd-Graber and Hal {Daum\'{e} III}},
	Booktitle = {NIPS Workshop on Learning Semantics},
	Location = {Montreal, Canada},
	Year = {2014},
	Title = {Generating Sentences from Semantic Vector Space Representations},
}

Jordan Boyd-Graber, Brianna Satinoff, He He, and Hal Daumé III. Besting the Quiz Master: Crowdsourcing Incremental Classification Games. Empirical Methods in Natural Language Processing, 2012. [Presentation] [Data] [Bibtex]

@inproceedings{Boyd-Graber:Satinoff:He:Daume-III-2012,
	Author = {Jordan Boyd-Graber and Brianna Satinoff and He He and Hal {Daum\'{e} III}},
	Url = {docs/qb_emnlp_2012.pdf},
	Booktitle = {Empirical Methods in Natural Language Processing},
	Location = {Jeju, South Korea},
	Year = {2012},
	Title = {Besting the Quiz Master: Crowdsourcing Incremental Classification Games},
}

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