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Dan Jurafsky

Active 1989–2026

262
Papers
33,384
Citations
83
h-index
188
i10-index

Citations

Citations per year for Dan Jurafsky1930: 1 citations1967: 2 citations1969: 2 citations1978: 1 citations1980: 1 citations1990: 1 citations1992: 1 citations1998: 2 citations2002: 2 citations2003: 4 citations2004: 16 citations2005: 20 citations2006: 21 citations2007: 37 citations2008: 47 citations2009: 61 citations2010: 131 citations2011: 158 citations2012: 290 citations2013: 337 citations2014: 398 citations2015: 477 citations2016: 608 citations2017: 821 citations2018: 1,176 citations2019: 1,338 citations2020: 1,405 citations2021: 1,558 citations2022: 1,432 citations2023: 2,266 citations2024: 2,937 citations2025: 3,389 citations2026: 1,407 citations1931–1966: no citations, so these years are not shown1968: no citations, so this year is not shown1970–1977: no citations, so these years are not shown1979: no citations, so this year is not shown1981–1989: no citations, so these years are not shown1991: no citations, so this year is not shown1993–1997: no citations, so these years are not shown1999–2001: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 5,231 citing papers, 29.1% of this breakdownChina: 2,567 citing papers, 14.3% of this breakdownUnited Kingdom: 1,329 citing papers, 7.4% of this breakdownGermany: 1,046 citing papers, 5.8% of this breakdownCanada: 640 citing papers, 3.6% of this breakdownIndia: 466 citing papers, 2.6% of this breakdownJapan: 413 citing papers, 2.3% of this breakdownNetherlands: 405 citing papers, 2.3% of this breakdownAustralia: 403 citing papers, 2.2% of this breakdownFrance: 403 citing papers, 2.2% of this breakdownItaly: 387 citing papers, 2.2% of this breakdownHong Kong: 335 citing papers, 1.9% of this breakdown
0%29.1%Other 24.1%

Institutions

Fields

  • Computer Science70.1%
  • Social Sciences8.7%
  • Medicine3.6%
  • Psychology3.5%
  • Engineering2.9%
  • Decision Sciences2.4%
  • Other8.8%

Topics

  • Topic Modeling14.6%
  • Natural Language Processing Techniques10.2%
  • Multimodal Machine Learning Applications3.3%
  • Advanced Text Analysis Techniques2.6%
  • Speech and dialogue systems2.4%
  • Sentiment Analysis and Opinion Mining2.4%
  • Other64.5%

Coauthors

All papers

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  1. On the Opportunities and Risks of Foundation Models

    Authors: Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Demszky, Dora, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tong Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Ahmad Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Benjamin T. Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon-Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Yang Wang and 14 more - arXiv (Cornell University), CoRR 2021 cited by 4,828

  2. KTO: Model Alignment as Prospect Theoretic Optimization

    Authors: Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff, Dan Jurafsky, Douwe Kiela - arXiv (Cornell University), CoRR 2024 cited by 715

  3. Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study

    Authors: Travis Zack, Eric Lehman, Mirac Süzgün, Jorge A. Rodriguez, Leo Anthony Celi, Judy Wawira Gichoya, Dan Jurafsky, Peter Szolovits, David W. Bates, Raja-Elie E. Abdulnour, Atul J. Butte, Emily Alsentzer - The Lancet Digital Health 2023 cited by 454

  4. Generalization through Memorization: Nearest Neighbor Language Models

    Authors: Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, Mike Lewis - ICLR 2020 cited by 1,098

  5. Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions

    Authors: Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Zou - ICLR 2024 cited by 416

  6. Racial disparities in automated speech recognition

    Authors: Allison Koenecke, Andrew Nam, Emily Lake, Joe Nudell, Minnie Quartey, Zion Mengesha, Connor Toups, John R. Rickford, Dan Jurafsky, Sharad Goel - National Academy of Sciences, Proc. Natl. Acad. Sci. USA 2020 cited by 672

  7. When and Why Vision-Language Models Behave like Bags-Of-Words, and What to Do About It?

    Authors: Mert Yüksekgönül, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, James Zou - ICLR 2023 cited by 668

  8. Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypes

    Authors: Nikhil Garg, Londa Schiebinger, Dan Jurafsky, James Zou - National Academy of Sciences, Proc. Natl. Acad. Sci. USA 2018 cited by 1,092

  9. AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders

    Authors: Zhengxuan Wu, Aryaman Arora, Atticus Geiger, Zheng Wang, Jing Huang, Dan Jurafsky, Christopher D. Manning, Christopher Potts - ICML 2025 cited by 197

  10. AI generates covertly racist decisions about people based on their dialect

    Authors: Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky, Sharese King - Nature, Nat. 2024 cited by 171

  11. ReFT: Representation Finetuning for Language Models

    Authors: Zhengxuan Wu, Aryaman Arora, Zheng Wang, Atticus Geiger, Dan Jurafsky, Christopher D. Manning, Christopher Potts - Advances in Neural Information Processing Systems 37, NeurIPS 2024 cited by 201

  12. Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models

    Authors: Myra Cheng, Esin Durmus, Dan Jurafsky - Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL (1) 2023 cited by 95

  13. Understanding Neural Networks through Representation Erasure

    Authors: Jiwei Li, Will Monroe, Dan Jurafsky - arXiv (Cornell University), CoRR 2016 cited by 479

  14. Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory

    Authors: Mirac Suzgun, Mert Yüksekgönül, Federico Bianchi, Dan Jurafsky, James Zou - Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), EACL (Volume 1: Long Papers) 2026 cited by 72

  15. Navigating the Grey Area: How Expressions of Uncertainty and Overconfidence Affect Language Models

    Authors: Kaitlyn Zhou, Dan Jurafsky, Tatsunori Hashimoto - Conference on Empirical Methods in Natural Language Processing, EMNLP 2023 cited by 82

  16. Foundation Models and Fair Use

    Authors: Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang - J. Mach. Learn. Res. 2023 cited by 81

  17. Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale

    Authors: Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan - ACM Conference on Fairness, FAccT 2023 cited by 263

  18. How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis

    Authors: Federico Bianchi, Patrick John Chia, Mert Yüksekgönül, Jacopo Tagliabue, Dan Jurafsky, James Zou - ICML 2024 cited by 112

  19. Community Interaction and Conflict on the Web

    Authors: Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky - World Wide Web Conference on World Wide Web - WWW '18 2018 cited by 312

  20. Dialect prejudice predicts AI decisions about people's character, employability, and criminality

    Authors: Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky, Sharese King - arXiv (Cornell University), CoRR 2024 cited by 60

  21. Social Bias Frames: Reasoning about Social and Power Implications of Language

    Authors: Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A. Smith, Yejin Choi - Meeting of the Association for Computational Linguistics, ACL 2020 cited by 100

  22. Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning

    Authors: Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau - arXiv (Cornell University), CoRR 2020 cited by 307

  23. Measuring the Evolution of a Scientific Field through Citation Frames

    Authors: David Jurgens, Srijan Kumar, Raine Hoover, Daniel A. McFarland, Dan Jurafsky - Transactions of the Association for Computational Linguistics, Trans. Assoc. Comput. Linguistics 2018 cited by 208

  24. Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change

    Authors: William L. Hamilton, Jure Leskovec, Dan Jurafsky - Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL (1) 2016 cited by 860