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Daniel E. Ho

Active 2005–2026

91
Papers
18,270
Citations
26
h-index
46
i10-index

Citations

Citations per year for Daniel E. Ho1977: 1 citations2002: 1 citations2004: 2 citations2005: 6 citations2006: 2 citations2007: 6 citations2008: 20 citations2009: 24 citations2010: 28 citations2011: 35 citations2012: 33 citations2013: 44 citations2014: 44 citations2015: 37 citations2016: 49 citations2017: 64 citations2018: 50 citations2019: 244 citations2020: 302 citations2021: 446 citations2022: 761 citations2023: 1,405 citations2024: 2,127 citations2025: 2,218 citations2026: 843 citations1978–2001: no citations, so these years are not shown2003: no citations, so this year is not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 2,555 citing papers, 29% of this breakdownChina: 794 citing papers, 9% of this breakdownUnited Kingdom: 735 citing papers, 8.3% of this breakdownGermany: 526 citing papers, 6% of this breakdownCanada: 414 citing papers, 4.7% of this breakdownItaly: 283 citing papers, 3.2% of this breakdownAustralia: 251 citing papers, 2.9% of this breakdownNetherlands: 232 citing papers, 2.6% of this breakdownFrance: 229 citing papers, 2.6% of this breakdownSwitzerland: 207 citing papers, 2.4% of this breakdownSpain: 171 citing papers, 1.9% of this breakdownJapan: 154 citing papers, 1.8% of this breakdown
0%29%Other 25.6%

Institutions

Fields

  • Computer Science44.9%
  • Medicine18.2%
  • Social Sciences10.7%
  • Engineering5.1%
  • Biochemistry, Genetics and Molecular Biology3.6%
  • Decision Sciences2.4%
  • Other15.1%

Topics

  • Topic Modeling5.9%
  • Artificial Intelligence in Healthcare and Education3.2%
  • Natural Language Processing Techniques3.2%
  • Ethics and Social Impacts of AI2.8%
  • Multimodal Machine Learning Applications2.4%
  • Explainable Artificial Intelligence (XAI)2.3%
  • Other80.2%

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. MatchIt: Nonparametric Preprocessing for Parametric Causal Inference

    Authors: Daniel E. Ho, Kosuke Imai, Gary King, Elizabeth A. Stuart - Journal of Statistical Software 2011 cited by 4,366

  3. Advances, challenges and opportunities in creating data for trustworthy AI

    Authors: Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou - Nature Machine Intelligence, Nat. Mach. Intell. 2022 cited by 517

  4. LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

    Authors: Neel Guha, Julian Nyarko, Daniel E. Ho, Christopher Ré, Adam Chilton, Aditya Narayana, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel N. Rockmore, Diego Zambrano, Dmitry Talisman, Enam Hoque, Faiz Surani, Frank Fagan, Galit Sarfaty, Gregory M. Dickinson, Haggai Porat, Jason Hegland, Jessica Wu, Joe Nudell, Joel Niklaus, John J. Nay, Jonathan H. Choi, Kevin Tobia, Margaret Hagan, Megan Ma, Michael A. Livermore, Nikon Rasumov-Rahe, Nils Holzenberger, Noam Kolt, Peter Henderson, Sean Rehaag, Sharad Goel, Shang Gao, Spencer Williams, Sunny Gandhi, Tom Zur, Varun Iyer, Zehua Li - NeurIPS 2023 cited by 468

  5. Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models

    Authors: Andy K. Zhang, Neil Perry, Riya Dulepet, Eliot Jones, Justin W. Lin, Joey Ji, Celeste Menders, Gashon Hussein, Samantha Liu, Donovan Jasper, Pura Peetathawatchai, Ari Glenn, Vikram Sivashankar, Daniel Zamoshchin, Leo Glikbarg, Derek Askaryar, Mike Yang, Teddy Zhang, Rishi Alluri, Nathan Tran, Rinnara Sangpisit, Polycarpos Yiorkadjis, Kenny Osele, Gautham Raghupathi, Dan Boneh, Daniel E. Ho, Percy Liang - ICLR 2025 cited by 143

  6. Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference

    Authors: Daniel E. Ho, Kosuke Imai, Gary King, Elizabeth A. Stuart - Political Analysis 2007 cited by 4,349

  7. How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals

    Authors: Eric Q. Wu, Kevin Wu, Roxana Daneshjou, David Ouyang, Daniel E. Ho, James Zou - Nature Medicine 2021 cited by 462

  8. Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

    Authors: Varun Magesh, Faiz Surani, Matthew Dahl, Mirac Suzgun, Christopher D. Manning, Daniel E. Ho - arXiv (Cornell University), CoRR 2024 cited by 83

  9. MatchIt: Nonparametric Preprocessing for Parametric Causal Inference

    Authors: Daniel E. Ho, Kosuke Imai, Gary King, Elizabeth A. Stuart, Noah Greifer - CRAN: Contributed Packages 2005 cited by 1,230

  10. When does pretraining help?: assessing self-supervised learning for law and the CaseHOLD dataset of 53, 000+ legal holdings

    Authors: Lucia Zheng, Neel Guha, Brandon Anderson, Peter Henderson, Daniel E. Ho - Eighteenth International Conference on Artificial Intelligence and Law, ICAIL 2021 cited by 127

  11. How well do LLMs cite relevant medical references? An evaluation framework and analyses

    Authors: Kevin Wu, Eric Wu, Ally Cassasola, Angela Zhang, Kevin Wei, Teresa Nguyen, Sith Riantawan, Patricia Shi Riantawan, Daniel E. Ho, James Zou - arXiv (Cornell University), CoRR 2024 cited by 57

  12. On the Societal Impact of Open Foundation Models

    Authors: Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K. Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan - arXiv (Cornell University), CoRR 2024 cited by 59

  13. Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice

    Authors: A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Kevin Klyman, Matthew Jagielski, Katja Filippova, Ken Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Eleni Triantafillou, Peter Kairouz, Nicole Mitchell, Niloofar Mireshghallah, Abigail Z. Jacobs, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Ilia Shumailov, Andreas Terzis, Solon Barocas, Jennifer Wortman Vaughan, danah boyd, Yejin Choi, Sanmi Koyejo, Fernando A. Delgado, Percy Liang, Daniel E. Ho, Pamela Samuelson, Miles Brundage, David Bau, Seth Neel, Hanna M. Wallach, Amy Cyphert, Mark A. Lemley, Nicolas Papernot, Katherine Lee - NeurIPS 2025 cited by 47

  14. Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models

    Authors: Matthew Dahl, Varun Magesh, Mirac Suzgun, Daniel E. Ho - The Journal of Legal Analysis 2024 cited by 192

  15. Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

    Authors: Peter Henderson, Mark S. Krass, Lucia Zheng, Neel Guha, Christopher D. Manning, Dan Jurafsky, Daniel E. Ho - Advances in Neural Information Processing Systems 35, NeurIPS 2022 cited by 156

  16. Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance

    Authors: Inioluwa Deborah Raji, Peggy Xu, Colleen Honigsberg, Daniel E. Ho - AAAI/ACM Conference on AI, AIES 2022 cited by 97

  17. Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies

    Authors: David Freeman Engstrom, Daniel E. Ho, Catherine M. Sharkey, Mariano-Florentino Cuéllar - 2020 cited by 249

  18. Extracting memorized pieces of (copyrighted) books from open-weight language models

    Authors: A. Feder Cooper, Aaron Gokaslan, Ahmed Ahmed, Amy Cyphert, Christopher De, Mark A. Lemley, Daniel E. Ho, Percy Liang, Percy Liang - ArXiv.org, CoRR 2025 cited by 27

  19. A Reasoning-Focused Legal Retrieval Benchmark

    Authors: Lucia Zheng, Neel Guha, Javokhir Arifov, Sarah Zhang, Michal Skreta, Christopher D. Manning, Peter Henderson, Daniel E. Ho - Symposium on Computer Science and Law on ZZZ, CSLAW 2025 cited by 24

  20. BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systems

    Authors: Andy K. Zhang, Joey Ji, Celeste Menders, Riya Dulepet, Thomas Qin, Ron Yifeng Wang, Junrong Wu, Kyleen Liao, Jiliang Li, Jinghan Hu, Sara Hong, Nardos Demilew, Shivatmica Murgai, Jason Tran, Nishka Kacheria, Ethan Ho, Denis Liu, Lauren McLane, Olivia Bruvik, Dai-Rong Han, Seungwoo Kim, Akhil Vyas, Cuiyuanxiu Chen, Ryan Li, Weiran Xu, Jonathan Z. Ye, Prerit Choudhary, Siddharth M. Bhatia, Vikram Sivashankar, Yuxuan Bao, Dawn Song, Dan Boneh, Daniel E. Ho, Percy Liang - NeurIPS 2025 cited by 35

  21. Implications of predicting race variables from medical images

    Authors: James Zou, Judy Wawira Gichoya, Daniel E. Ho, Ziad Obermeyer - Science 2023 cited by 29

  22. Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools

    Authors: Emily Black, Rakshit Naidu, Rayid Ghani, Kit T. Rodolfa, Daniel E. Ho, Hoda Heidari - Equity and Access in Algorithms, EAAMO 2023 cited by 17

  23. LegalBench: Prototyping a Collaborative Benchmark for Legal Reasoning

    Authors: Neel Guha, Daniel E. Ho, Julian Nyarko, Christopher Ré - arXiv (Cornell University), CoRR 2022 cited by 22

  24. When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset

    Authors: Lucia Zheng, Neel Guha, Brandon R. Anderson, Peter Henderson, Daniel E. Ho - arXiv (Cornell University), CoRR 2021 cited by 35