Dan Jurafsky Publications

Travis Zack, Eric Lehman, Mirac Suzgun, Jorge A Rodriguez, Leo Anthony Celi, Judy Gichoya, Dan Jurafsky, Peter Szolovits, David W Bates, Raja-Elie E Abdulnour, Atul Butte, Emily Alsentzer. 2024. Assessing the potential of GPT-4 to perpetuat racial and gender biases in health care: a model evaluation study. The Lancet Digital Health, 6:1, e12-e22.

Connor Toups, Rishi Bommasani, Kathleen Creel, Sarah Bana, Dan Jurafsky, Percy Liang. 2023. Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes. NeurIPS 2023.

Peter Henderson*, Eric Mitchell*, Christopher Manning, Dan Jurafsky, Chelsea Finn. Self-Destructing Models: Increasing the Costs of Harmful Dual Uses in Foundation Models. AAAI/ACM Conference on AI, Ethics, and Society, 2023. Honorable Mention for Best Student Paper

Eugenia H. Rho, Maggie Harrington, Yuyang Zhong, Reid Pryzant, Nicholas P. Camp, Dan Jurafsky, and Jennifer L. Eberhardt. 2023. Escalated police stops of Black men are linguistically and psychologically distinct in their earliest moments. PNAS 120 (23).

Anjalie Field, Prateek Verma, Nay San, Jennifer L. Eberhardt, and Dan Jurafsky. 2023. Developing Speech Processing Pipelines for Police Accountability. Proceedings of INTERSPEECH 2023.

Kaitlyn Zhou, Dan Jurafsky, and Tatsunori Hashimoto. 2023. Navigating the Grey Area: Expressions of Overconfidence and Uncertainty in Language Models . EMNLP 2023.

Isabel Papadimitriou and Dan Jurafsky. 2023. Injecting structural hints: Using language models to study inductive biases in language learning. Findings of EMNLP 2023

Tolúlọpẹ́ Ògúnrẹ̀mí, Christopher D. Manning, and Dan Jurafsky. 2023. Multilingual self-supervised speech representations improve the speech recognition of low-resource African languages with codeswitching. Proceedings of Sixth Workshop on Computational Approaches to Linguistic Code-Switching.

Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang. 2023. Foundation Models and Fair Use. Journal of Machine Learning Research, 2023

Mirac Suzgun, Stuart M. Shieber, Dan Jurafsky. 2023. string2string: A Modern Python Library for String-to-String Algorithms. Preprint. arXiv 2023

Myra Cheng, Esin Durmus and Dan Jurafsky. 2023. Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models. ACL 2023. ACL 2023 Social Impact Award.

Martijn Bartelds, Nay San, Bradley McDonnell, Dan Jurafsky and Martijn Wieling. 2023. Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data Augmentation. ACL 2023.

Mirac Suzgun, Luke Melas-Kyriazi, Dan Jurafsky. 2023. Follow the Wisdom of the Crowd: Effective Text Generation via Minimum Bayes Risk Decoding. Findings of ACL 2023.

Dorottya Demszky, Jing Liu, Heather Hill, Dan Jurafsky, Chris Piech. 2023. Can Automated Feedback Improve Teachers’ Uptake of Student Ideas? Evidence From a Randomized Controlled Trial In a Large-Scale Online Course. (Also public draft version here). Educational Evaluation and Policy Analysis, 2023 Nov.

Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan. 2023. Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. ACM Conference on Fairness, Accountability and Transparency (2023)

Mert Yuksekgonul, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, James Zou. 2023. When and why Vision-Language Models behave like Bags-of-Words, and what to do about it? International Conference on Learning Representations (ICLR 2023).

Faisal Ladhak, Esin Durmus, Mirac Suzgun, Tianyi Zhang, Dan Jurafsky, Kathleen McKeown and Tatsunori Hashimoto. 2023. When Do Pre-Training Biases Propagate to Downstream Tasks? A Case Study in Text Summarization. Proceedings of EACL 2023.

Tolúlọpẹ́ Ògúnrẹ̀mí, Dan Jurafsky and Christopher D. Manning. 2023. Mini But Mighty: Efficient Multilingual Pretraining with Linguistically-Informed Data Selection. Findings of EACL 2023.

Isabel Papadimitriou*, Kezia Lopez*, and Dan Jurafsky. 2023. Multilingual BERT has an accent: Evaluating English influences on fluency in multilingual models. Findings of EACL 2023, and SIGTYP 2023

San, N., Bartelds, M., Billings, B., De Falco, E., H., F., Safri, J., Sahrozi, W., Foley, B., McDonnell, B., & Jurafsky, D. (2023). Leveraging supplementary text data to kick-start automatic speech recognition system development with limited transcriptions. In Proceedings of the Sixth Workshop on the Use of Computational Methods in the Study of Endangered Languages (ComputEL-6). Association for Computational Linguistics.

Yiwei Luo, Beth Levin and Dan Jurafsky. Taking sides using sentential complement predicates: The interplay of factivity and politeness in persuasion. Proceedings of the 97th Annual Meeting of the Linguistic Society of America. 2023.

Peter Henderson, Mark S. Krass, Lucia Zheng, Neel Guha, Christopher D. Manning, Dan Jurafsky, and Daniel E. Ho. 2022. Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Proceedings of Neurips 2022. [pdf]

Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang. 2022. Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS), 2022. [pdf]

Eric Mitchell*, Peter Henderson*, Christopher Manning, Dan Jurafsky, Chelsea Finn. 2022. Self-Destructing Models: Increasing the Costs of Harmful Dual Uses in Foundation Models. New Frontiers in Adversarial Machine Learning Workshop at ICML and Pre-training: Perspectives, Pitfalls, and Paths Forward at ICML, 2022. [pdf]

Mirac Suzgun, Luke Melas-Kyriazi and Dan Jurafsky. 2022. Prompt-and-Rerank: A Method for Zero-Shot and Few-Shot Arbitrary Textual Style Transfer with Small Language Models. Proceedings of EMNLP 2022. [pdf] [bib]

Kawin Ethayarajh and Dan Jurafsky. 2022. The Authenticity Gap in Human Evaluation. EMNLP 2022. [pdf] [bib]

Dallas Card, Serina Chang, Chris Becker, Julia Mendelsohn, Rob Voigt, Leah Boustan, Ran Abramitzky, and Dan Jurafsky. 2022. Computational analysis of 140 years of US political speeches reveals more positive but increasingly polarized framing of immigration. Proceedings of the National Academy of Sciences 119 (31) e2120510119. [pdf]

Sterling Alic, Dorottya Demszky, Zid Mancenido, Jing Liu, Heather Hill & Dan Jurafsky. 2022. Computationally Identifying Funneling and Focusing Questions in Classroom Discourse . 17th Workshop on Innovative Use of NLP for Building Educational Applications (BEA) [pdf] [bib]

Kaitlyn Zhou, Kawin Ethayarajh, Dallas Card, Dan Jurafsky. 2022. Problems with Cosine as a Measure of Embedding Similarity for High Frequency Words. ACL 2022. [pdf] [bib].

Kaitlyn Zhou, Kawin Ethayarajh, Dan Jurafsky. 2022. Richer Countries and Richer Representations. ACL 2022 - Findings. [pdf] [bib].

San, N., Bartelds, M., Ògúnrèmí, T., Mount, A., Thompson, R., Higgins, M., Barker, R., Simpson, J., & Jurafsky, D. 2022. Automated speech tools for helping communities process restricted-access corpora for language revival efforts. In Proceedings of the 5th workshop on the use of Computational Methods in the Study of Endangered Languages (ComputEL-5). [pdf]

Junshen Chen, Dallas Card, and Dan Jurafsky. 2022. Modular Domain Adaptation. ACL 2022 - Findings. [pdf] [bib].

Stephan Risi, Crystal Lee, Mathias W. Nielsen, Emma Kerr, Emer Brady, Lanu Kim, Daniel A. McFarland, Dan Jurafsky, James Zou, and Londa Schiebinger. 2022. Diversifying History: A Large-Scale Analysis of Changes in Researcher Demographics and Scholarly Agendas. PlosOne. 17(1). [pdf].

Bradley P. Turnwald, Margaret A. Perry, David Jurgens, Vinodkumar Prabhakaran, Dan Jurafsky, Hazel R. Markus, Alia J. Crum. 2022. Language in popular American culture constructs the meaning of healthy and unhealthy eating: Narratives of craveability, excitement, and social connection in movies, television, social media, recipes, and food reviews, Appetite, Volume 172. [pdf]

Portelance, Eva, Michael C. Frank, Dan Jurafsky, Alessandro Sordoni, Romain Laroche. (2021). The Emergence of the Shape Bias Results from Communicative Efficiency. Proceedings of the 25th Conference on Computational Natural Language Learning (CoNLL). [pdf] [bib]

Nay San, Martijn Bartelds, Mitchell Browne, Lily Clifford, Fiona Gibson, John Mansfield, David Nash, Jane Simpson, Myfany Turpin, Maria Vollmer, Sasha Wilmoth, and Dan Jurafsky. 2021. Leveraging pre-trained representations to improve access to untranscribed speech from endangered languages. ASRU 2021. [pdf] [bib]

Dorottya Demszky, Jing Liu, Heather Hill, Dan Jurafsky, and Chris Piech. (2021). Can Automated Feedback Improve Teachers' Uptake of Student Ideas? Evidence From a Randomized Controlled Trial In a Large-Scale Online Course. EdWorkingPapers. [pdf]

William Held, Dan Iter, Dan Jurafsky. (2021). Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference. EMNLP 2021. [pdf] [bib]

Rishi Bommasani, full list of authors, Percy Liang. 2021. On the Opportunities and Risks of Foundation Models. [pdf]

Heidi Chen, Emma Pierson, Sonja Schmer-Galunder, Jonathan Altamirano, Dan Jurafsky, Jure Leskovec, Magali Fassiotto, and Nishita Kothary. 2021. Gender differences in patient perceptions of physicians' communal traits and the impact on physician evaluations. Journal of Women's Health, April 2021. 551-556. http://doi.org/10.1089/jwh.2019.8233. [bib]

Mauriello M.L., Tantivasadakarn N., Mora-Mendoza M. A., Lincoln E. T., Hon G., Nowruzi P., Simon D., Hansen L., Goenawan N. H. , Kim J., Gowda N., Jurafsky D., Paredes P. E. (2021). A Suite of Mobile Conversational Agents for Daily Stress Management (Popbots): Mixed Methods Exploratory Study. JMIR Form Res 2021;5(9):e25294 doi: 10.2196/25294. [pdf].

Mauriello, M.L., Lincoln, E.T., Hon, G., Simon, D., Jurafsky, D., and Paredes, P.E. (2021)."SAD: A Stress Annotated Dataset for Recognizing Everyday Stressors in SMS-like Conversational Systems." In Proceedings of ACM CHI 2021 Conference on Human Factors in Computing Systems. Extended Abstract. [pdf]

Camp, N.P., Voigt, R., Jurafsky, D., and Eberhardt, J.L. (2021). The Thin Blue Waveform: Racial disparities in officer prosody shape institutional trust. Journal of Personality and Social Psychology 121(6), 1157-1171. [bib]

Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather Hill, Dan Jurafsky, and Tatsunori Hashimoto. 2021. Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions. ACL 2021. [pdf] [bib]

Kawin Ethayarajh and Dan Jurafsky. 2021. Attention Flows are Shapley Value Explanations. ACL 2021. [pdf] [bib]

Michael Hahn, Dan Jurafsky, Richard Futrell. 2021. Sensitivity as a Complexity Measure for Sequence Classification Tasks. Transactions of the Association for Computational Linguistics 9:891-908. [paper] [bib]

Yasuhide Miura, Yuhao Zhang, Emily Tsai, Curtis Langlotz and Dan Jurafsky. 2021. Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). [paper, bib]

Reid Pryzant, Dallas Card, Dan Jurafsky, Victor Veitch and Dhanya Sridhar. 2021. Causal Effects of Linguistic Properties. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). [paper, bib]

Urvashi Khandelwal, Angela Fan, Dan Jurafsky, Luke Zettlemoyer and Mike Lewis. 2021. Nearest Neighbor Machine Translation. International Conference on Learning Representations (ICLR), 2021. [pdf] [bib]

K. Mahowald, M. Norris, D. Jurafsky. 2021. Concord begets concord: A Bayesian model of nominal concord typology. Proceedings of 95th LSA (2021).

Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau. 2020. Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning. Journal of Machine Learning Research 21(248):1-43, 2020.

Alex Tamkin, Dan Jurafsky, and Noah Goodman. 2020. Language Through a Prism: A Spectral Approach for Multiscale Language Representations. NeurIPS 2020.

Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald and Dan Jurafsky. 2020. With Little Power Comes Great Responsibility. EMNLP 2020. [pdf] [supplementary] [bib]

Kawin Ethayarajh and Dan Jurafsky. 2020. Utility is in the Eye of the User: A Critique of NLP Leaderboards. EMNLP 2020. [pdf] [bib]

Yiwei Luo, Dallas Card, and Dan Jurafsky. 2020. Detecting Stance in Media On Global Warming. Findings of the ACL: EMNLP 2020. [pdf] [bib]

Isabel Papadimitriou and Dan Jurafsky. 2020. Learning Music Helps You Read: Using transfer to study linguistic structure in language models EMNLP 2020 [pdf] [bib]

Turnwald, B.P., Anderson, K.G., Jurafsky, D., and Crum, A.J. (2020). Five-star prices, appealing healthy item descriptions? Expensive restaurants' descriptive menu language. Health Psychology. [pdf]

Li Lucy, Dora Demszky, Patricia Bromley, Dan Jurafsky. 2020. Content Analysis of Textbooks via Natural Language Processing: Findings on Gender, Race, and Ethnicity in Texas U.S. History Textbooks. AERA Open 2020. 2020 Education Data Science Conference Best Paper Award. [pdf]

Julia Mendelsohn, Yulia Tsvetkov and Dan Jurafsky. 2020. A framework for the computational linguistic analysis of dehumanization. Frontiers in Artificial Intelligence. [pdf].

Dan Iter, Kelvin Guu, Larry Lansing, Dan Jurafsky. 2020. Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models. ACL 2020.

Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A Smith and Yejin Choi. 2020. Social Bias Frames: Reasoning about Social and Power Implications of Language. ACL (2020)

Adam S. Miner, Albert Haque, Jason A. Fries, Scott L. Fleming, Denise E. Wilfley, G. Terence Wilson, Arnold Milstein, Dan Jurafsky, Bruce A. Arnow, W. Stewart Agras, Li Fei-Fei, and Nigam H. Shah. 2020. Assessing the accuracy of automatic speech recognition for psychotherapy. npj Digital Medicine 3, 82 (2020).

Bas Hofstra, Vivek V. Kulkarni, Sebastian Munoz-Najar Galvez, Bryan He, Dan Jurafsky, and Daniel A. McFarland. 2020. The Diversity-Innovation Paradox in Science. Proceedings of the National Academy of Sciences. [pdf]

Allison Koenecke, Andrew Nam, Emily Lake, Joe Nudell, Minnie Quartey, Zion Mengesha, Connor Toups, John Rickford, Dan Jurafsky, and Sharad Goel. 2020. Racial Disparities in Automated Speech Recognition. Proceedings of the National Academy of Sciences 117 (14) 7684-7689. [pdf] [Press: NY Times]

Michael Hahn, Dan Jurafsky, and Richard Futrell. 2020. Universals of word order reflect optimization of grammars for efficient communication. Proceedings of the National Academy of Sciences 117 (5) 2347-2353. [pdf] [bib] [code]

Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer and Mike Lewis. 2020. Generalization through Memorization: Nearest Neighbor Language Models. International Conference on Learning Representations (ICLR), 2020. [pdf] [code]

Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi, Dan Jurafsky, Diyi Yang. 2020. Automatically Neutralizing Subjective Bias in Text. AAAI, 2020 [pdf] [code]

Julia Kruk, Jonah Lubin, Karan Sikka, Xiao Lin, Dan Jurafsky, and Ajay Divakaran. 2019. Integrating Text and Image: Determining Multimodal Document Intent in Instagram Posts. EMNLP 2019. [pdf]

Yiwei Luo, Dan Jurafsky, and Beth Levin. 2019. From Insanely Jealous to Insanely Delicious: Computational Models for the Semantic Bleaching of English Intensifiers. Proceedings of the ACL Workshop on Computational Approaches to Historical Language Change. [pdf] [bib]

Dorottya Demszky, Nikhil Garg, Rob Voigt, James Zou, Matthew Gentzkow, Jesse Shapiro and Dan Jurafsky. 2019. Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings. NAACL 2019.   [pdf] [bib]

Lerrigo, Robert, Johnny T. R. Coffey, Joshua L. Kravitz, Priyanka Jadhav, Azadeh Nikfarjam, Nigam H. Shah, Dan Jurafsky, and Sidhartha R. Sinha. The Emotional Toll of Inflammatory Bowel Disease: Using Machine Learning to Analyze Online Community Forum Discourse. Crohn's & Colitis 360 1, no. 2 (2019).

Urvashi Khandelwal, Kevin Clark, Dan Jurafsky, and Łukasz Kaiser. 2019. Sample Efficient Text Summarization Using a Single Pre-Trained Transformer. ArXiv Preprint.

Ignacio Cases, Clemens Rosenbaum, Matthew Riemer, Atticus Geiger, Tim Klinger, Alex Tamkin, Olivia Li, Sandhini Agarwal, Joshua Greene, Dan Jurafsky, Christopher Potts and Lauri Karttunen. 2019. Recursive Routing Networks: Learning to Compose Modules for Language Understanding. NAACL 2019.   [pdf] [bib]

Diyi Yang, Jiaao Chen, Zichao Yang, Dan Jurafsky, and Eduard Hovy. 2019. Let's Make Your Request More Persuasive: Modeling Persuasive Strategies via Semi-Supervised Neural Nets on Crowdfunding Platforms. NAACL 2019.   [pdf] [bib]

Diyi Yang, Robert Kraut, Tenbroeck Smith, Elijah Mayfield, and Dan Jurafsky. 2019. Seekers, Providers, Welcomers, and Storytellers: Modeling Social Roles in Online Health Communities. CHI, 2019 (Best Paper Honorable Mention).   [pdf] [bib]

Beth Levin, Lelia Glass, and Dan Jurafsky. 2019. Systematicity in the semantics of noun compounds: The role of artifacts vs. natural kinds. Linguistics Vol 7 Issue 3, 429-472. [pdf]

Joseph Lee, Ziang Xie, Cindy Wang, Max Drach, Dan Jurafsky, and Andrew Y. Ng. 2019. Neural Text Style Transfer via Denoising and Reranking. Proceedings of the ACL 2019 Workshop on Methods for Optimizing and Evaluating Neural Language Generation (NeuralGen), pages 74-81 [pdf]

William L. Hamilton, Marinka Zitnik, Payal Bajaj, Dan Jurafsky, Jure Leskovec. 2018. Embedding Logical Queries on Knowledge Graphs. Proceedings of NeurIPS. 2018.

Matthew Lamm, Arun Tejasvi Chaganty, Chrisopher D. Manning, Dan Jurafsky and Percy Liang. 2018. Textual Analogy Parsing: What's Shared and What's Compared among Analogous Facts. EMNLP 2018. [paper, bib]

Anjalie Field, Doron Kliger, Shuly Wintner, Jennifer Pan, Dan Jurafsky and Yulia Tsvetkov. 2018. Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies. EMNLP 2018. [paper, bib]

Vinodkumar Prabhakaran, Camilla Griffiths, Hang Su, Prateek Verma, Nelson Morgan, Jennifer Eberhardt, and Dan Jurafsky. 2018. Detecting Institutional Dialog Acts in Police Traffic Stops. Transactions of the Association for Computational Linguistics 6: 467--481. [paper, bib]

David Jurgens, Srijan Kumar, Raine Hoover, Dan McFarland, Dan Jurafsky. 2018 Measuring the Evolution of a Scientific Field through Citation Frames. Transactions of the Association for Computational Linguistics (TACL). [pdf] [website (with data)] [code]

Urvashi Khandelwal, He He, Peng Qi and Dan Jurafsky. 2018. Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context. Association for Computational Linguistics (ACL). [paper, bib]

Michael Hahn, Judith Degen, Noah Goodman, Dan Jurafsky and and Richard Futrell. 2018. An information-theoretic explanation of adjective ordering preferences. 40th Annual Meeting of the Cognitive Science Society (CogSci). [paper, bib]

Dan Iter, Jong H. Yoon and Dan Jurafsky. 2018. Automatic Detection of Incoherent Speech for Diagnosing Schizophrenia. NAACL HLT Workshop on Computational Linguistics and Clinical Psychology. [paper, bib]

Nikhil Garg, Londa Schiebinger, Dan Jurafsky, James Zou. 2018. Word embeddings quantify 100 years of gender and ethnic stereotypes. Proceedings of the National Academy of Sciences 2018.

Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky. 2018. Community Interaction and Conflict on the Web. Proceedings of the Web Conference (WWW) 2018.

Reid Pryzant, Kelly Shen, Dan Jurafsky and Stefan Wagner. 2018. Deconfounded Lexicon Induction for Interpretable Social Science. 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). [paper]

Ziang Xie, Guillaume Genthial, Stanley Xie, Andrew Y. Ng, and Dan Jurafsky. 2018. Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction. 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2018). [paper]

Reid Pryzant, Young-joo Chung, Denny Britz, Dan Jurafsky. 2018. JESC: Japanese-English Subtitle Corpus. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC), 2018. [paper] [dataset]

Rob Voigt, David Jurgens, Vinodkumar Prabhakaran, Dan Jurafsky, and Yulia Tsvetkov. 2018. RtGender: A Corpus of Responses to Gender for Studying Gender Bias. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC), 2018. [paper]

David Jurgens, Yulia Tsvetkov, and Dan Jurafsky. 2017. Writer Profiling Without the Writer's Text. Proceedings of the 9th International Conference on Social Informatics (SocInfo). [pdf preprint]

Jiwei Li, Will Monroe, Tianlin Shi, Sebastien Jean, Alan Ritter and Dan Jurafsky. 2017. Adversarial Learning for Neural Dialogue Generation. Proceedings of EMNLP 2017.

Jiwei Li and Dan Jurafsky. 2017. Neural Net Models of Open-Domain Discourse Coherence. Proceedings of EMNLP 2017.

Rob Voigt, Nicholas P. Camp, Vinodkumar Prabhakaran, William L. Hamilton, Rebecca C. Hetey, Camilla M. Griffiths, David Jurgens, Dan Jurafsky, and Jennifer L. Eberhardt. 2017. Language from police body camera footage shows racial disparities in officer respect. PNAS. Winner of the Cozzarelli Prize and the Cialdini Prize.

Reid Pryzant, Young-joo Chung, Dan Jurafsky. 2017. Predicting Sales from the Language of Product Descriptions. SIGIR eCom.

Felix Muzny, Mark Algee-Hewitt, and Dan Jurafsky. 2017. Dialogism in the novel: A computational model of the dialogic nature of narration and quotations. Digital Scholarship in the Humanities.

Jiwei Li, Will Monroe and Dan Jurafsky. 2017. Understanding Neural Networks through Representation Erasure [arxiv]

Jiwei Li, Will Monroe and Dan Jurafsky. 2017. Learning to Decode for Future Success. [arxiv][code for dialogue parts]

Jiwei Li, Will Monroe and Dan Jurafsky. 2017. Data Distillation for Controlling Specificity in Dialogue Generation [arxiv]

Jiwei Li, Will Monroe and Dan Jurafsky. 2017. A Simple, Fast Diverse Decoding Algorithm for Neural Generation. [arxiv]

David Jurgens, Yulia Tsvetkov, and Dan Jurafsky. 2017. Incorporating Dialectal Variability for Socially Equitable Language Identification. To appear in Proceedings of ACL 2017, Vancouver. [pdf]

Brad Turnwald, Dan Jurafsky, Alana Connor, and Alia Crum, (2017). Reading between the menu lines: Are restaurants' descriptions of "healthy" foods unappealing? Health Psychology. [Advance pdf]

Ziang Xie, Sida I. Wang, Jiwei Li, Daniel Lévy, Aiming Nie, Dan Jurafsky, Andrew Y. Ng. 2017. Data Noising as Smoothing in Neural Network Language Models. Proceedings of ICLR 2017.

Heeyoung Lee, Mihai Surdeanu, and Dan Jurafsky. 2017. A scaffolding approach to coreference resolution integrating statistical and rule-based models. Natural Language Engineering. [pre-publication pdf version].

Justine Zhang, William L. Hamilton, Cristian Danescu-Niculescu-Mizil, Jure Leskovec, Dan Jurafsky. 2017. Community Identity and User Engagement in a Multi-Community Landscape. Proceedings of ICWSM 2017

William L. Hamilton, Justine Zhang, Cristian Danescu-Niculescu-Mizil, Jure Leskovec, Dan Jurafsky. 2017. Loyalty in Online Communities. Proceedings of ICWSM 2017 (short paper).

Felix Muzny, Michael Fang, Angel X. Chang and Dan Jurafsky. 2017. A Two-stage Sieve Approach for Quote Attribution. Proceedings of the European Chapter of the Association for Computational Linguistics (EACL) 2017, Valencia, Spain. [pdf, bib, data]

Andrew L. Maas, Peng Qi, Ziang Xie, Awni Y. Hannun, Christopher T. Lengerich, Daniel Jurafsky, Andrew Y. Ng. 2017. Building DNN acoustic models for large vocabulary speech recognition. Computer Speech & Language, Volume 41, Pages 195-213. [Earlier ArXiv version]

Rob Voigt, Penelope Eckert, Dan Jurafsky and Robert J. Podesva. 2016. Cans and cants: Computational potentials for multimodality with a case study in head position. Journal of Sociolinguistics 20/5, 2016: 677--711 [pdf]

Dan Jurafsky, Victor Chahuneau, Bryan R. Routledge, Noah A. Smith. 2016. Linguistic Markers of Status in Food Culture: Bourdieu's Distinction in a Menu Corpus. Journal of Cultural Analytics 2016.

William L. Hamilton, Jure Leskovec, Dan Jurafsky. 2016. Cultural Shift or Linguistic Drift? Comparing Two Computational Models of Semantic Change. Proceedings of EMNLP 2016. [pdf]

William L. Hamilton, Kevin Clark, Jure Leskovec, Dan Jurafsky. 2016. Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora. Proceedings of EMNLP 2016. [pdf].

Ruihong Huang, Ignacio Cases, Dan Jurafsky, Cleo Condoravdi and Ellen Riloff. 2016. Distinguishing Past, On-going, and Future Events: The EventStatus Corpus. Proceedings of EMNLP 2016. [pdf]

Jiwei Li, Will Monroe, Alan Ritter, Michel Galley, Jianfeng Gao and Dan Jurafsky. 2016. Deep Reinforcement Learning for Dialogue Generation. Proceedings of EMNLP 2016.

Rob Voigt, Dan Jurafsky, and Meghan Sumner. 2016. Between- and Within-Speaker Effects of Bilingualism on F0 Variation. Proceedings of Interspeech. [pdf]

Dan Jurafsky. 2016. "Tea." Encyclopedia of Chinese Language and Linguistics. Rint Sybesma, Wolfgang Behr, Yueguo Gu, Zev Handel, C.-T. James Huang, and James Myers (Eds). Leiden: Brill. [pdf]

William L. Hamilton, Jure Leskovec, and Dan Jurafsky. 2016. Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. Proceedings of ACL. [pdf]

Vinodkumar Prabhakaran, William L. Hamilton, Dan McFarland, and Dan Jurafsky. 2016. Predicting the Rise and Fall of Scientific Topics from Trends in their Rhetorical Framing. Proceedings of ACL 2016. [pdf]

Jiwei Li, Xinlei Chen, Eduard Hovy and Dan Jurafsky. 2016. Visualizing and Understanding Neural Models in NLP. Proceedings of NAACL 2016. [pdf]

Kao, Justine T. and Dan Jurafsky. 2015. A computational analysis of poetic style: Imagism and its influence on modern professional and amateur poetry. Linguistic Issues in Language Technology 12:3, 1-31 [pdf] [bib]

Jiwei Li and Dan Jurafsky. 2015. Do Multi-Sense Embeddings Improve Natural Language Understanding? Proceedings of EMNLP 2015. [pdf, bib]

Jiwei Li, Minh-Thang Luong, Dan Jurafsky and Eduard Hovy. 2015. When Are Tree Structures Necessary for Deep Learning of Representations? Proceedings of EMNLP 2015. [pdf, bib]

Podesva, Robert J., Patrick Callier, Rob Voigt, and Dan Jurafsky. 2015. The connection between smiling and GOAT fronting: Embodied affect in sociophonetic variation. Proceedings of the International Congress of Phonetic Sciences 18. [pdf] [bib]

Jiwei Li, Thang Luong, and Dan Jurafsky. 2015. A Hierarchical Neural Autoencoder for Paragraphs and Documents. Proceedings of ACL 2015. [pdf] [bib]

Rob Voigt and Dan Jurafsky. 2015. The Users Who Say "Ni": Audience Identification in Chinese-language Restaurant Reviews. Proceedings of ACL 2015. [pdf] [bib]

Andrew L. Maas, Ziang Xie, Dan Jurafsky, and Andrew Y. Ng. 2015. Lexicon-Free Conversational Speech Recognition with Neural Networks. Proceedings of NAACL 2015. [pdf] [bib]

Dan Jurafsky. 2014. Obituary for Charles J. Fillmore. Computational Linguistics 40:3, 724-723. [pdf] [bib]

Sebastian Schuster, Stephanie Pancoast, Milind Ganjoo, Michael C. Frank, and Dan Jurafsky. 2014. Speaker-Independent Detection of Child-Directed Speech. Proceedings of the IEEE Workshop on Spoken Language Technology (SLT-2014). [pdf] [bib] [github]

Dan Jurafsky, Victor Chahuneau, Bryan R. Routledge, and Noah A. Smith. 2014. Narrative framing of consumer sentiment in online restaurant reviews. First Monday 19:4. [bib]
   [Press: NPR All Things Considered, Wash. Post, SF Chronicle, etc.]

Tim Althoff, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky. 2014. How to Ask for a Favor: A Case Study on the Success of Altruistic Requests. AAAI ICWSM 2014 [pdf] [bib] [data]
   [Press: Technology Review, Huffington Post, Fast Company, Gizmodo, ABC News]

Heeyoung Lee, Mihai Surdeanu, Bill MacCartney, and Dan Jurafsky. 2014. On the Importance of Text Analysis for Stock Price Prediction. Proceedings of the Language Resources and Evaluation Conference (LREC), 2014. [pdf] [bib] [data]

Vogel, Adam, Andrés Gómez Emilsson, Michael C. Frank, Dan Jurafsky and Christopher Potts. 2014. Learning to reason pragmatically with cognitive limitations. In Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 3055-3060. [pdf] [bib] [data]

Elie Bursztein, Angelique Moscicki, Celine Fabry, Steven Bethard, John C. Mitchell, and Dan Jurafsky. 2014. Easy Does It: More Usable CAPTCHAs. Proceedings of ACM CHI 2014. [pdf] [bib]
  [Press: Help Net Security ]

Kevin Reschke, Martin Jankowiak, Mihai Surdeanu, Christopher D. Manning, and Daniel Jurafsky. 2014. Event Extraction Using Distant Supervision. Proceedings of the Language Resources and Evaluation Conference (LREC), 2014. [pdf] [bib]

Rob Voigt, Robert J. Podesva and Dan Jurafsky. 2014. Body Movement Correlates with Prosodic Indicators of Engagement. Proceedings of Speech Prosody 2014. [pdf] [bib]

Valentin I. Spitkovsky, Hiyan Alshawi, and Daniel Jurafsky. 2013. Breaking Out of Local Optima with Count Transforms and Model Recombination: A Study in Grammar Induction. EMNLP 2013. [pdf, bib; best paper award ]

Heeyoung Lee, Angel Chang, Yves Peirsman, Nathanael Chambers, Mihai Surdeanu, and Dan Jurafsky. 2013. Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules. Computational Linguistics 39:4, 885-916.

Dan Jurafsky. 2013. Why Ice Cream Sounds Fat and Crackers Sound Skinny. Stanford Magazine July/August 2013

Daniel Cer, Christopher D. Manning and Dan Jurafsky. 2013. Positive Diversity Tuning for Machine Translation System Combination. Proceedings of the Eighth Workshop on Statistical Machine Translation (WMT 2013) [pdf, bib ]

McFarland, Daniel A., Christopher D. Manning, Daniel Ramage, Jason Chuang, Jeffrey Heer, and Dan Jurafsky. 2013. Differentiating Language Usage Through Topic Models. Poetics 41 (6), 607-625

McFarland, Daniel A., Dan Jurafsky, and Craig M. Rawlings. 2013. Making the Connection: Social Bonding in Courtship Situations. American Journal of Sociology Vol. 118, No. 6, 1596-1649. Roger V. Gould Prize [pdf, bib]

Cristian Danescu-Niculescu-Mizil, Robert West, Dan Jurafsky, Jure Leskovec, Christopher Potts. 2013. No country for old members: User lifecycle and linguistic change in online communities. Proceedings of WWW 2013. Best paper award. [pdf, bib]

Adam Vogel, Christopher Potts, and Dan Jurafsky. 2013. Implicatures and Nested Beliefs in Approximate Decentralized-POMDPs. In Proceedings of ACL 2013. [pdf, bib]

Kevin Reschke, Adam Vogel, and Dan Jurafsky. 2013. Generating Recommendation Dialogs by Extracting Information from User Reviews. ACL 2013 [pdf, bib]

Cristian Danescu-Niculescu-Mizil, Moritz Sudhof, Dan Jurafsky, Jure Leskovec, and Christopher Potts. 2013. A computational approach to politeness with application to social factors. Proceedings of ACL, 2013. [pdf, bib]

Marta Recasens, Cristian Danescu-Niculescu-Mizil, and Dan Jurafsky. 2013. Linguistic Models for Analyzing and Detecting Biased Language. 2013. Proceedings of ACL 2013. [pdf, bib]

Marta Recasens, Matthew Can, and Dan Jurafsky. 2013. Same Referent, Different Words: Unsupervised Mining of Opaque Coreferent Mentions. Proceedings of NAACL 2013. [pdf, bib; data]

Vogel, Adam, Max Bodoia, Dan Jurafsky, and Christopher Potts. 2013. Emergence of Gricean maxims from multi-agent decision theory. Proceedings of HLT NAACL 2013. [pdf, bib]

Rob Voigt and Dan Jurafsky. 2013. Tradition and Modernity in 20th Century Chinese Poetry. NAACL Second Workshop on Computational Linguistics for Literature.

Rajesh Ranganath, Dan Jurafsky, and Daniel A. McFarland. 2013. Detecting friendly, flirtatious, awkward, and assertive speech in speed-dates. Computer Speech and Language. 27:1, 89-115. [pdf, bib]

J. J. McAuley, J. Leskovec, D. Jurafsky. 2012. Learning attitudes and attributes from multi-aspect reviews. International Conference on Data Mining

Valentin I. Spitkovsky, Hiyan Alshawi, and Daniel Jurafsky. 2012. Bootstrapping Dependency Grammar Inducers from Incomplete Sentence Fragments via Austere Models. In Proceedings of the 11th International Conference on Grammatical Inference (ICGI 2012).

Heeyoung Lee, Marta Recasens, Angel Chang, Mihai Surdeanu, and Dan Jurafsky. 2012. Joint Entity and Event Coreference Resolution across Documents. In Proceedings of the Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL).

Valentin I. Spitkovsky, Hiyan Alshawi, and Daniel Jurafsky. 2012. Three Dependency-and-Boundary Models for Grammar Induction.. EMNLP-CoNLL 2012.

Adam Vogel and Dan Jurafsky. 2012. He Said, She Said: Gender in the ACL Anthology. ACL Workshop on Rediscovering 50 Years of Discoveries.

Ashton Anderson, Dan McFarland, and Dan Jurafsky. 2012 Towards a Computational History of the ACL: 1980-2008. ACL Workshop on Rediscovering 50 Years of Discoveries.

Justine Kao and Dan Jurafsky. 2012. A Computational Analysis of Style, Affect, and Imagery in Contemporary Poetry. NAACL Workshop on Computational Linguistics for Literature.

Rob Voigt and Dan Jurafsky. 2012. Towards a Literary Machine Translation: The Role of Referential Cohesion. NAACL Workshop on Computational Linguistics for Literature.

Valentin I. Spitkovsky, Hiyan Alshawi, and Daniel Jurafsky. 2012. Capitalization Cues Improve Dependency Grammar Induction. In NAACL HLT 2012 Workshop on Inducing Linguistic Structure (WILS 2012)

Dan Jurafsky. 2012. The Cosmopolitan Condiment: An exploration of ketchup's Chinese origins Slate, May 30, 2012.

Gabor Angeli, Chris Manning, Dan Jurafsky. 2012. Parsing Time: Learning to Interpret Time Expressions. North American Chapter of the Association for Computational Linguistics (NAACL) 2012.

Michael Levin, Stefan Krawczyk, Steven Bethard, and Dan Jurafsky. 2012. Citation-based bootstrapping for large-scale author disambiguation. Journal of the American Society for Information Science and Technology 63:5, 1030-1047.

Joshua Freedman and Dan Jurafsky. 2011. Authenticity in America: Class Distinctions in Potato Chip Advertising. Gastronomica 11, 4: 46-54.

Dan Jurafsky. 2011. Macarons, Macaroons, Macaroni: The curious history. Slate, Nov 16, 2011

Valentin I. Spitkovsky, Hiyan Alshawi, Angel X. Chang, and Daniel Jurafsky. 2011. Unsupervised Dependency Parsing without Gold Part-of-Speech Tags. Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP 2011). [PDF]

Valentin I. Spitkovsky, Hiyan Alshawi, and Daniel Jurafsky. 2011. Lateen EM: Unsupervised Training with Multiple Objectives, Applied to Dependency Grammar Induction. Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP 2011). [PDF]

Nathanael Chambers and Dan Jurafsky. 2011. Template-Based Information Extraction without the Templates. ACL-2011, Portland, OR. [PDF]

Valentin I. Spitkovsky, Hiyan Alshawi, and Daniel Jurafsky. 2011. Punctuation: Making a Point in Unsupervised Dependency Parsing. In Proceedings of the Fifteenth Conference on Computational Natural Language Learning (CoNLL-2011) [PDF]

Heeyoung Lee, Yves Peirsman, Angel Chang, Nathanael Chambers, Mihai Surdeanu, Dan Jurafsky. 2011. Stanford's Multi-Pass Sieve Coreference Resolution System at the CoNLL-2011 Shared Task. Proceedings of CoNNL 2011.

Nikhil Johri, Daniel Ramage, Daniel A. McFarland, Dan Jurafsky. 2011. A Study of Academic Collaborations in Computational Linguistics using a Latent Mixture of Authors Model. In ACL 2011 Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities.

Ramesh Nallapati, Xiaolin Shi, Dan McFarland, Jure Leskovec and Daniel Jurafsky. 2011 LeadLag LDA: Estimating Topic Specific Leads and Lags of Information Outlets. Proceedings of ICWSM.

Andrey Gusev, Nathanael Chambers, Divye Raj Khilnani, Pranav Khaitan, Steven Bethard, and Dan Jurafsky. 2011. Using query patterns to learn the duration of events. In International Conference on Computational Semantics, 2011. [PDF]

Xiaolin Shi, Ramesh Nallapati, Jure Lescovec, Dan McFarland and Dan Jurafsky. 2010. Who Leads Whom: Topical Lead-Lag analysis across corpora. NIPS Workshop on Computational Social Science and Wisdom of Crowds.

Adam Vogel, Karthik Raghunathan, and Dan Jurafsky. Eye Spy: Improving Vision through Dialog. Dialog with Robots: Papers from the AAAI Fall Symposium (FS-10-05). [PDF]

Sasha Calhoun, Jean Carletta, Jason M. Brenier, Neil Mayo, Dan Jurafsky, Mark Steedman, and David Beaver. 2010. The NXT-format Switchboard Corpus: a rich resource for investigating the syntax, semantics, pragmatics and prosody of dialogue. Language Resources & Evaluation 44:387-419. DOI 10.1007/s10579-010-9120-1. [PDF]

Karthik Raghunathan, Heeyoung Lee, Sudarshan Rangarajan, Nathanael Chambers, Mihai Surdeanu, Dan Jurafsky, Christopher Manning. A Multi-Pass Sieve for Coreference Resolution. Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing (EMNLP-2010), 2010. [PDF]

Steven Bethard and Dan Jurafsky. 2010. Who should I cite? Learning literature search models from citation behavior. In ACM Conference on Information and Knowledge Management. [PDF]

Valentin I. Spitkovsky, Daniel Jurafsky, and Hiyan Alshawi. 2010. Profiting from Mark-Up: Hyper-Text Annotations for Guided Parsing. In Proceedings of ACL-2010, Uppsala, Sweden. [PDF]

Adam Vogel and Dan Jurafsky. 2010. Learning to Follow Navigational Directions. In Proceedings of ACL-2010, Uppsala, Sweden. [PDF]

Nathanael Chambers and Dan Jurafsky. 2010. Improving the Use of Pseudo-Words for Evaluating Selectional Preferences. ACL-2010, Uppsala, Sweden. [PDF]

Elie Bursztein, Steven Bethard, John C. Mitchell, Dan Jurafsky, and Celine Fabry. How good are humans at solving CAPTCHAs? A large scale evaluation. In IEEE Symposium on Security and Privacy, 2010. [PDF]

Daniel Cer, Michel Galley, Daniel Jurafsky and Christopher Manning. 2010. Phrasal: A Toolkit for Statistical Machine Translation with Facilities for Extraction and Incorporation of Arbitrary Model Features. Proceedings of NAACL 2010 Demo Session. [PDF]

Daniel Cer , Daniel Jurafsky and Christopher Manning. 2010. The Best Lexical Metric for Phrase-Based Statistical MT System Optimization. Proceedings of NAACL 2010. [PDF]

Sharon Goldwater, Dan Jurafsky, and Christopher D. Manning. 2010. Which words are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates. Speech Communication 52, 181-200. [PDF]

Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jurafsky, and Christopher D. Manning. 2010. Viterbi Training Improves Unsupervised Dependency Parsing. In Proceedings of CoNLL-2010. [PDF].

Valentin I. Spitkovsky, Hiyan Alshawi, and Daniel Jurafsky. 2010. From Baby Steps to Leapfrog: How “Less is More” in Unsupervised Dependency Parsing. In Proceedings of NAACL HLT 2010. [PDF].

Daniel Cer, Marie-Catherine de Marneffe, Daniel Jurafsky and Christopher D. Manning. 2010. Parsing to Stanford Dependencies: Trade-offs between speed and accuracy. In Proceedings of LREC-10, Malta. [PDF]

Nathanael Chambers and Dan Jurafsky. 2010. A Database of Narrative Schemas. Proceedings of LREC-2010, Malta. [PDF]

Sebastian Pado, Daniel Cer, Michel Galley, Dan Jurafsky and Christopher D. Manning. 2009. Measuring Machine Translation Quality as Semantic Equivalence: A Metric Based on Entailment Features. Machine Translation 23:2-3, 181-193. doi:10.1007/s10590-009-9060-y

Yun-Hsuan Sung and Dan Jurafsky. 2009. Hidden Conditional Random Fields for Phone Recognition. ASRU 2009. [PDF]

Yuan Zhao and Dan Jurafsky. 2009. The effect of lexical frequency and Lombard reflex on tone hyperarticulation. Journal of Phonetics 27:2, 231-247. [PDF]

Valentin I. Spitkovsky, Hiyan Alshawi, and Daniel Jurafsky. 2009. Baby Steps: How “Less is More” in Unsupervised Dependency Parsing.
In NIPS 2009 Workshop on Grammar Induction, Representation of Language and Language Learning. [PDF].

Eneko Agirre, Angel X. Chang, Daniel S. Jurafsky, Christopher D. Manning, Valentin I. Spitkovsky, and Eric Yeh. 2009. Stanford-UBC at TAC-KBP. In Proceedings of the Second Text Analysis Conference TAC 2009). [PDF].

Mike Mintz, Steven Bills, Rion Snow, and Dan Jurafsky. 2009. Distant supervision for relation extraction without labeled data. Proceedings of ACL-IJCNLP 2009. [PDF]

Nathanael Chambers and Dan Jurafsky. 2009. Unsupervised Learning of Narrative Schemas and their Participants. Proceedings of ACL-IJCNLP 2009. [PDF]

Rajesh Ranganath, Dan Jurafsky, and Dan McFarland. 2009. It's Not You, it's Me: Detecting Flirting and its Misperception in Speed-Dates. Proceedings of EMNLP 2009. [PDF]

Sebastian Padó, Michel Galley, Dan Jurafsky, and Chris Manning. 2009. Robust Machine Translation Evaluation with Entailment Features. Proceedings of ACL-IJCNLP 2009.

Dan Jurafsky, Rajesh Ranganath, and Dan McFarland. 2009. Extracting Social Meaning: Identifying Interactional Style in Spoken Conversation. Proceedings of NAACL HLT 2009. [PDF]

Pi-Chuan Chang, Huihsin Tseng, Dan Jurafsky, and Christopher D. Manning. 2009. Discriminative Reordering with Chinese Grammatical Relations Features. NAACL 2009 Third Workshop on Syntax and Structure in Statistical Translation.

Sebastian Padó, Michel Galley, Dan Jurafsky, and Christopher D. Manning. 2009. Textual Entailment Features for Machine Translation Evaluation. Proceedings of the EACL 2009 Fourth Workshop on Statistical Machine Translation.

Pi-Chuan Chang, Dan Jurafsky and Christopher D. Manning. 2009. Disambiguating "DE" for Chinese-English Machine Translation. Proceedings of the EACL 2009 Fourth Workshop on Statistical Machine Translation.

Alan Bell, Jason Brenier, Michelle Gregory, Cynthia Girand, and Dan Jurafsky. 2009. Predictability Effects on Durations of Content and Function Words in Conversational English. Journal of Memory and Language 60:1, 92-111.

David Hall, Daniel Jurafsky, and Christopher D. Manning. 2008. Studying the History of Ideas Using Topic Models. In Proceedings of EMNLP 2008, 363-371.

Rion Snow, Brendan O'Connor, Daniel Jurafsky and Andrew Y. Ng. 2008. Cheap and Fast - But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks. In Proceedings of EMNLP 2008, 254-263.

Nathanael Chambers and Dan Jurafsky. 2008. Jointly Combining Implicit Constraints Improves Temporal Ordering. In Proceedings of EMNLP 2008, 698-706.

Sharon Goldwater, Dan Jurafsky, and Christopher D. Manning. 2008. Which words are hard to recognize? Lexical, prosodic, and disfluency factors that increase ASR error rates. In ACL/HLT; 380-388.

Nathanael Chambers and Dan Jurafsky. 2008. Unsupervised Learning of Narrative Event Chains. In Proceedings of ACL/HLT 2008.

Daniel Cer, Daniel Jurafsky, and Christopher D. Manning. 2008. Regularization and Search for Minimum Error Rate Training. Proceedings of the Third Workshop on Statistical Machine Translation. [PDF]

Yun-Hsuan Sung, Constantinos Boulis, and Dan Jurafsky. 2008. Maximum Conditional Likelihood Linear Regression and Maximum A Posteriori for Hidden Conditional Random Fields Speaker Adaptation. IEEE ICASSP 2008, 4293-4296.

Vivek Kumar Rangarajan Sridhar, Ani Nenkova, Shrikanth Narayanan and Dan Jurafsky. 2008. Detecting prominence in conversational speech: pitch accent, givenness and focus. In Proceedings of Speech Prosody, Campinas, Brazil, 453-456.

Yun-Hsuan Sung, Constantinos Boulis, Christopher Manning and Dan Jurafsky. 2007. Regularization, Adaptation, and Non-Independent Features Improve Hidden Conditional Random Fields for Phone Classification. In IEEE ASRU 2007. 347-352.

Rion Snow, Sushant Prakash, Daniel Jurafsky, and Andrew Y. Ng. Learning to merge word senses. In Proceedings of EMNLP 2007

Surabhi Gupta, John Niekrasz, Matthew Purver and Dan Jurafsky. 2007. Resolving "You" in Multi-Party Dialog. In Proceedings of the 8th SIGdial Workshop on Discourse and Dialogue, Antwerp, Belgium, September 2007.

Volker Strom, Ani Nenkova, Robert Clark, Yolanda Vazquez-Alvarez, Jason Brenier, Simon King, and Dan Jurafsky. 2007. Modelling Prominence and Emphasis Improves Unit-Selection Synthesis. Interspeech 2007.

Nathanael Chambers, Shan Wang and Dan Jurafsky. 2007. Classifying Temporal Relations Between Events. Proceedings of ACL 2007 short papers, Prague, Czech Republic.

Surabhi Gupta, Matthew Purver and Dan Jurafsky. 2007. Disambiguating Between Generic and Referential "You" in Dialog. Proceedings of ACL 2007 short papers, Prague, Czech Republic.

Surabhi Gupta, Ani Nenkova and Dan Jurafsky. 2007. Measuring Importance and Query Relevance in Topic-focused Multi-document Summarization. Proceedings of ACL 2007 short papers, Prague, Czech Republic.

Ani Nenkova, Jason Brenier, Anubha Kothari, Sasha Calhoun, Laura Whitton, David Beaver, and Dan Jurafsky. 2007. To Memorize or to Predict: Prominence Labeling in Conversational Speech. NAACL-HLT 2007.

Yuan Zhao and Dan Jurafsky. 2007. The Effect of Lexical Frequency on Tone Production. Proceedings of ICPhS 2007, 477-480.

Rion Snow, Dan Jurafsky, and Andrew Y. Ng. 2006. Semantic taxonomy induction from heterogenous evidence. Proceedings of COLING/ACL 2006, Sydney. ACL Best Paper Award.

Constance Clarke and Dan Jurafsky. 2006. Limitations of MLLR Adaptation with Spanish-Accented English: An Error Analysis. Proceedings of INTERSPEECH-2006, Pittsburgh, PA.

Filip Krsmanovic, Curtis Spencer, Daniel Jurafsky, and Andrew Y. Ng. 2006 Have we met? MDP Based Speaker ID for Robot Dialogue. Proceedings of INTERSPEECH-2006, Pittsburgh, PA.

Cheng-Tao Chu, Yun-Hsuan Sung, Yuan Zhao, Dan Jurafsky. 2006. Detection of Word Fragments in Mandarin Telephone Conversation. Proceedings of INTERSPEECH-2006, Pittsburgh, PA.

Jason Brenier, Ani Nenkova, Anubha Kothari, Laura Whitton, David Beaver, Dan Jurafsky. 2006. The (Non)Utility of Linguistic Features for Predicting Prominence in Spontaneous Speech. IEEE/ACL 2006 Workshop on Spoken Language Technology, Aruba.

Rion Snow, Daniel Jurafsky, and Andrew Y. Ng. 2005. Learning syntactic patterns for automatic hypernym discovery . Proceedings of NIPS 17.

Steven Bethard, Hong Yu, Ashley Thornton, Vasileios Hatzivassiloglou, and Dan Jurafsky. Extracting opinion propositions and opinion holders using syntactic and lexical cues. In James G. Shanahan, Yan Qu, and Janyce Wiebe, editors, Computing Attitude and Affect in Text: Theory and Applications. Springer, 2005

Sameer Pradhan, Kadri Hacioglu, Valerie Krugler, Wayne Ward , James H. Martin and Daniel Jurafsky. 2005. Support Vector Learning for Semantic Argument Classification. Machine Learning 60:1-3 , 11-39

Yuan, Jiahong and Dan Jurafsky. 2005. Detection of Questions in Chinese Conversation . In Proceedings of IEEE ASRU 2005.

Yuan, Jiahong, Jason M. Brenier, and Dan Jurafsky. 2005. Pitch Accent Prediction: Effects of Genre and Speaker. In Proceedings of EUROSPEECH-05.

Huihsin Tseng, Pichuan Chang, Galen Andrew, Daniel Jurafsky, Christopher Manning. 2005. A Conditional Random Field Word Segmenter. Proceedings of the Fourth SIGHAN Workshop on Chinese Language Processing.

Huihsin Tseng, Daniel Jurafsky, Christopher Manning. 2005. Morphological features help POS tagging of unknown words across language varieties. Proceedings of the Fourth SIGHAN Workshop on Chinese Language Processing.

Jason M. Brenier, Daniel Cer and Daniel Jurafsky. 2005. The Detection of Emphatic Words Using Acoustic and Lexical Features. In Proceedings of EUROSPEECH-05.

Yanli Zheng, Richard Sproat, Liang Gu, Izhak Shafran, Haolang Zhou, Yi Su, Dan Jurafsky, Rebecca Starr and Su-Youn Yoon. 2005. Accent Detection and Speech Recognition for Shanghai-Accented Mandarin. In Proceedings of EUROSPEECH-05.

Yuan Zhao and Dan Jurafsky. 2005. A preliminary study of Mandarin filled pauses. Proceedings of DiSS'05, Disfluency in Spontaneous Speech Workshop.

Pradhan, Sameer, Wayne Ward, Kadri Hacioglu, Jim Martin, Dan Jurafsky. 2005. Semantic Role Labeling Using Different Syntactic Views. Proceedings of ACL-2005, Ann Arbor, MI.

Chen, Ying, Hongling Sun, and Dan Jurafsky. 2005. A corrigendum to Sun and Jurafsky (2004) "Shallow Semantic Parsing of Chinese. University of Colorado at Boulder CSLR Tech Report TR-CSLR-2005-01.

Narayanan, Srini, and Daniel Jurafsky. 2004. A Bayesian Model of Human Sentence Processing. Unpublished manuscript.

Susanne Gahl, Daniel Jurafsky, and Douglas Roland. 2004. Verb subcategorization frequencies: American English corpus data, methodological studies, and cross-corpus comparisons. Behavior Research Methods, Instruments, & Computers, 36, 432-443.

Diab, Mona, Kadri Hacioglu, and Daniel Jurafsky. 2004. Automatic Tagging of Arabic Text: From Raw Text to Base Phrase Chunks. In Proceedings of NAACL-HLT 2004.

Pradhan, Sameer, Honglin Sun, Wayne Ward, James H. Martin, and Daniel Jurafsky. 2004. Parsing Arguments of Nominalizations in English and Chinese. In Proceedings of NAACL-HLT 2004.

Pradhan, Sameer, Wayne Ward, Kadri Hacioglu, James H. Martin, and Daniel Jurafsky. 2004. Shallow Semantic Parsing Using Support Vector Machines. In Proceedings of NAACL-HLT 2004.

Steven Bethard, Hong Yu, Ashley Thornton, Vasieleios Hativassiloglou, and Dan Jurafsky. 2004. Automatic Extraction of Opinion Propositions and their Holders. In Proceedings of AAAI Spring Symposium on Exploring Attitude and Affect in Text.

Honglin Sun and Daniel Jurafsky. 2004. Shallow Semantic Parsing of Chinese. In Proceedings of NAACL-HLT 2004. [see corrections in Chen, Sun, and Jurafsky 2005 above]

Alan Bell, Daniel Jurafsky, Eric Fosler-Lussier, Cynthia Girand, Michelle Gregory, and Daniel Gildea. 2003. Effects of disfluencies, predictability, and utterance position on word form variation in English conversation. Journal of the Acoustical Society of America 113 (2), 1001-1024. (PDF)

Jurafsky, Daniel. 2003. Pragmatics and Computational Linguistics. In Laurence R. Horn & Gregory Ward (eds.) Handbook of Pragmatics. Oxford: Blackwell. (Postscript) or (PDF) [this draft is a pre-final version, there are various changes in references and copy-editing in published version]

Jurafsky, Dan. 2003. Probabilistic Modeling in Psycholinguistics: Linguistic Comprehension and Production. In Rens Bod, Jennifer Hay, and Stefanie Jannedy, (Eds)., Probabilistic Linguistics (Postscript) or (PDF).

Pradhan, Sameer, Kadri Hacioglu, Wayne Ward, James H. Martin, and Daniel Jurafsky. 2003. Semantic Role Parsing: Adding Semantic Structure to Unstructured Text. In Proceedings of the International Conference on Data Mining (ICDM-2003).

Sun, Honglin and Dan Jurafsky. 2003. The Effect of Rhythm on Structural Disambiguation in Chinese. Proceedings of the Annual Conference of the Association of Computational Linguistics Special Interest Group on Chinese (SIGHAN-03). [PDF]

Ikeno, Ayako, Bryan Pellom, Dan Cer, Ashley Thornton, Jason M. Brenier, Dan Jurafsky, Wayne Ward, and William Byrne. 2003. Issues in Recognition of Spanish-Accented Spontaneous English. In Proceedings of IEEE/ISCA Workshop on Spontaneous Speech Processing and Recognition, Tokyo, Japan. (PDF).

Gahl, Susanne, Lise Menn, Gail Ramsberger, Daniel Jurafsky, Elizabeth Elder, Molly Rewega and Audrey Holland. 2003. Syntactic frame and verb bias in aphasia: Plausibility judgments of undergoer-subject sentences. Brain and Cognition 53:2, 223-228. (PDF).

Daniel Gildea and Daniel Jurafsky. 2002. Automatic Labeling of Semantic Roles Computational Linguistics 28:3, 245-288.

Jurafsky, Daniel, Alan Bell, and Cynthia Girand. 2002. The Role of the Lemma in Form Variation. In Gussenhoven, Carlos and Natasha Warner (eds.), Papers in Laboratory Phonology VII. Berlin/New York: Mouton de Gruyter, 1-34. (Postscript) or (PDF).

Roland, Douglas and Daniel Jurafsky. (2002). Verb sense and verb subcategorization probabilities. In Stevenson, Suzanne, and Paola Merlo (eds.), The Lexical Basis of Sentence Processing: Formal, Computational, and Experimental Issues. Amsterdam: John Benjamins. 325-346. (Postscript) or (PDF).

Gildea, Daniel and Daniel Jurafsky (2002). Identifying Semantic Relations in Text. In Gerhard Lakemeyer and Bernhard Nebel (eds.) Exploring AI in the New Millenium. Morgan Kaufmann.

Narayanan, Srini and Daniel Jurafsky. 2002. A Bayesian Model Predicts Human Parse Preference and Reading Time in Sentence Processing. In T. G. Dietterich, S. Becker and Z. Ghahramani (Eds.), Advances in Neural Information Processing Systems 14. Cambridge, MA: MIT Press. 59-65. (Postscript) (PDF)

Sameer S Pradhan, Gabriel Illouz, Sasha J Blair-Goldensohn, Andrew Hazen Schlaikjer, Valerie Krugler, Elena Filatova, Pablo A Duboue, Hong Yu, Rebecca J Passonneau, Steven Bethard, Vasileios Hatzivassiloglou, Wayne Ward, Dan Jurafsky, Kathleen R McKeown, and James H Martin. 2002. Building a foundation system for producing short answers to factual questions. Eleventh Text Retrieval Conference (TREC-11). Washington, DC.

Wayne Ward, Holly Krech, Xiuyang Yu, Keith Herold, George Figgs, Ayako Ikeno, D an Jurafsky, and William Byrne. 2002. Lexicon adaptation for LVCSR: speaker idiosyncracies, non-native speakers, and pronunciation choice. In ISCA ITR Workshop on Pronunciation Modeling and Lexicon Adaptation, 2002.

Jurafsky, Daniel, Alan Bell, Michelle Gregory, and William D. Raymond. 2001. Probabilistic Relations between Words: Evidence from Reduction in Lexical Production. In Bybee, Joan and Paul Hopper (eds.). Frequency and the emergence of linguistic structure. Amsterdam: John Benjamins. 229-254. (Postscript) or (PDF).

Schone, Patrick and Daniel Jurafsky. 2001. Is Knowledge-Free Induction of Multiword Unit Dictionary Headwords a Solved Problem? Proceedings of Empirical Methods in Natural Language Processing, Pittsburgh, PA. (PDF)

Schone, Patrick and Daniel Jurafsky. 2001. Language-Independent Induction of Part of Speech Class Labels Using Only Language Universals. In IJCAI-2001 Workshop "Text Learning: Beyond Supervision". (Postscript) (PDF)

Schone, Patrick and Daniel Jurafsky. 2001. Knowlege-Free Induction of Inflectional Morphologies. Proceedings of the North American chapter of the Association for Computational Linguistics (NAACL-2001). (PDF)

Jurafsky, Dan, Wayne Ward, Zhang Jianping, Keith Herold, Yu Xiuyang, and Zhang Sen. 2001. What Kind of Pronunciation Variation is Hard for Triphones to Model? Proceedings of ICASSP-01, I.577-580, Salt Lake City, Utah. (Postscript) (PDF)

Jurafsky, Daniel, Alan Bell, Michelle Gregory, and William D. Raymond. 2001. The Effect of Language Model Probability on Pronunciation Reduction. In Proceedings of ICASSP-01 II.801--804, Salt Lake City, Utah. (Postscript) (PDF)

Stolcke, Andreas, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca Bates, Daniel Jurafsky, Paul Taylor, Rachel Martin, Marie Meteer, and Carol Van Ess-Dykema. 2000. Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech. Computational Linguistics 26:3, 339-371 (Postscript) or (PDF).

Schone, Patrick and Daniel Jurafsky. 2000. Knowlege-Free Induction of Morphology using Latent Semantic Analysis. Proceedings of the Conference on Computational Natural Language Learning (CoNLL-2000). (PDF)

Gildea, Daniel and Daniel Jurafsky. 2000. Automatic Labeling of Semantic Roles. In Proceedings of ACL 2000, Hong Kong. (Postscript) (PDF)

Roland, Douglas, Daniel Jurafsky, Lise Menn, Susanne Gahl, Elizabeth Elder and Chris Riddoch. 2000. Verb Subcategorization Frequency Differences between Business-News and Balanced Corpora: the role of verb sense. In Proceedings of the Association for Computational Linguistics (ACL-2000) Workshop on Comparing Corpora. (Postscript) or (PDF)

Gregory, Michelle L., William D. Raymond, Alan Bell, Eric Fosler-Lussier, and Daniel Jurafsky. 1999. The effects of collocational strength and contextual predictability in lexical production. Chicago Linguistics Society (CLS-99), 151-166. (Postscript) (MS Word)

Bell, Alan, Daniel Jurafsky, Eric Fosler-Lussier, Cynthia Girand, and Daniel Gildea. 1999. Forms of English function words - Effects of disfluencies, turn position, age and sex, and predictability. Proceedings of ICPhS-99. [PDF]

Mark Core, Masato Ishizaki, Johanna Moore, Christine Nakatani, Nobert Reithinger, David Traum, Syun Tutiya. 1999. The Report of The Third Workshop of the Discourse Resource Initiative. Chiba University. [PDF]

Shriberg, Elizabeth, Rebecca Bates, Paul Taylor, Andreas Stolcke, Daniel Jurafsky, Klaus Ries, Noah Coccaro, Rachel Martin, Marie Meteer, and Carol Van Ess-Dykema. 1998. Can Prosody Aid the Automatic Classification of Dialog Acts in Conversational Speech? Language and Speech 41:3-4, 439-487 [PDF]

Jurafsky, Daniel, Alan Bell, Eric Fosler-Lussier, Cynthia Girand, and William Raymond. 1998. Reduction of English function words in Switchboard. Proceedings of ICSLP-98, Volume 7, 3111-3114.

Coccaro, Noah and Daniel Jurafsky. 1998. Towards Better Integration of Semantic Predictors in Statistical Language Modeling Proceedings of ICSLP-98, Volume 6, 2403-2406.

Stolcke, Andreas, Elizabeth Shriberg, Rebecca Bates, Noah Coccaro, Daniel Jurafsky, Rachel Martin, Marie Meteer, Klaus Ries, Paul Taylor, and Carol Van Ess-Dykema. (1998 draft). Dialog Act Modeling for Conversational Speech. Papers from the AAAI Spring Symposium on Applying Machine Learning to Discourse Processing, TR SS-98-01, 98-105. AAAI Press.

Roland, Douglas, and Daniel Jurafsky. 1998. How Verb Subcategorization Frequencies Are Affected By Corpus Choice. In proceedings of COLING/ACL-98, 1122-1128. [PDF]

Jurafsky, Daniel, Elizabeth Shriberg, Barbara Fox, and Traci Curl. 1998. Lexical, Prosodic, and Syntactic Cues for Dialog Acts.Proceedings of ACL/COLING-98 Workshop on Discourse Relations and Discourse Markers, 114-120. (Postscript) or (PDF).

Fillmore, Charles, Nancy Ide, Daniel Jurafsky, and Catherine Macleod. 1998. An American National Corpus: A Proposal. In Proceedings of the First International Conference on Language Resources and Evaluation, Granada.

Narayanan, Srini, and Daniel Jurafsky. 1998. Bayesian Models of Human Sentence Processing. In Proceedings of CogSci-98. Marr Prize Honorable Mention.

Jurafsky, Daniel, Rebecca Bates, Noah Coccaro, Rachel Martin, Marie Meteer, Klaus Ries, Elizabeth Shriberg, Andreas Stolcke, Paul Taylor, and Carol Van Ess-Dykema. 1998. Switchboard Discourse Language Modeling Project Report Research Note 30, Center for Speech and Language Processing, Johns Hopkins University, Baltimore, MD. (Postscript) or (PDF).

Jurafsky, Daniel, Rebecca Bates, Noah Coccaro, Rachel Martin, Marie Meteer, Klaus Ries, Elizabeth Shriberg, Andreas Stolcke, Paul Taylor, and Carol Van Ess-Dykema. 1997. Automatic Detection of Discourse Structure for Speech Recognition and Understanding. In the Proceedings of the 1997 IEEE Workshop on Speech Recognition and Understanding, Santa Barbara. (Postscript) or (PDF).

Jurafsky, Daniel, Elizabeth Shriberg, and Debra Biasca. 1997a. Switchboard SWBD-DAMSL Shallow-Discourse-Function Annotation Coders Manual, Draft 13, University of Colorado, Boulder. Institute of Cognitive Science Technical Report 97-02. Postscript or HTML

Jurafsky, Daniel, Elizabeth Shriberg, and Debra Biasca. 1997b. Switchboard Dialog Act Corpus. Corpus can be downloaded here as swb1_dialogact_annot.tar.gz

Jurafsky, Daniel. (1996a). A Probabilistic Model of Lexical and Syntactic Access and Disambiguation. Cognitive Science 20 137-194 [PDF]

Jurafsky, Daniel (1996b). Universal Tendencies in the Semantics of the Diminutive. Language 72 533-578. [PDF]

Gildea, Daniel and Daniel Jurafsky. (1996). Learning Bias and Phonological Rule Induction. Computational Linguistics 22, 497-530. (PDF)

Gildea, Daniel and Daniel Jurafsky. 1995. Automatic Induction of Finite State Transducers for Simple Phonological Rules. In Proceedings of ACL 95, Cambridge, MA, pp 9-15

Tajchman, Gary and Dan Jurafsky and Eric Fosler. 1995. Learning Phonological Rule Probabilities from Speech Corpora with Exploratory Computational Phonology. In Proceedings of ACL 95, Cambridge, MA, pp 9-15

Tajchman, Gary and Eric Fosler and Dan Jurafsky. 1995. Building Multiple Pronunciation Models for Novel Words using Exploratory Computational Phonology. In Proceedings of EUROSPEECH-95

Jean-Pierre Koenig and Daniel Jurafsky. 1995. Type Underspecification and On-line Type Construction in the Lexicon. In Proceedings of WCCFL-94

Jurafsky, Daniel, Chuck Wooters, Gary Tajchman, Jonathan Segal, Andreas Stolcke, Eric Fosler, and Nelson Morgan. 1995. Using a Stochastic Context-Free Grammar as a Language Model for Speech Recognition. In Proceedings of ICASSP-95, Detroit, MI, pp 189-192 (PDF)

Jurafsky, Daniel, Chuck Wooters, Gary Tajchman, Jonathan Segal, Andreas Stolcke, Eric Fosler, and Nelson Morgan. 1994. The Berkeley Restaurant Project. In Proceedings of ICSLP-94 Yokohama, Japan. pp 2139-2142. (PDF)

Jurafsky, Daniel, Chuck Wooters, Gary Tajchman, Jonathan Segal, Andreas Stolcke, Eric Fosler, and Nelson Morgan. 1994. Integrating Experimental Models of Syntax, Phonology, and Accent/Dialect in a Speech Recognizer (in AAAI-94 workshop)

I also developed some (very old) bibtex macros for the LSA (Linguistic Society of America) style, in 1994. Here are the files: lsalike.bst and lsalike.sty.

Data related to the Switchboard Dialog Act Tagged Corpus:

• Jurafsky, Daniel, Elizabeth Shriberg, and Debra Biasca. 1997a. Switchboard SWBD-DAMSL Shallow-Discourse-Function Annotation Coders Manual, Draft 13, University of Colorado, Boulder. Institute of Cognitive Science Technical Report 97-02. Postscript or HTML

• Jurafsky, Daniel, Elizabeth Shriberg, and Debra Biasca. 1997b. Switchboard Dialog Act Corpus. Corpus can be downloaded here as swb1_dialogact_annot.tar.gz

• The training splits file ws97-train-convs.list used in Stolcke et al. (2000).

• The test splits file ws97-test-convs.list used in Stolcke et al. (2000).