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Percy Liang

Stanford University - Department of Computer Science

Gates Computer Science Building

353 Serra Mall

Stanford, CA 94305-9025

United States

  • Stanford University - Department of Computer Science

SCHOLARLY PAPERS

6

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5,352

TOTAL CITATIONS

13

Scholarly Papers (6)

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1.

Foundation Models and Fair Use

Stanford Law and Economics Olin Working Paper No. 584
Number of pages: 77 Posted: 13 Apr 2023 Last Revised: 22 Aug 2023
Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley and Percy Liang
Princeton University - Center for Information Technology Policy, Stanford University - Stanford University, Students, Stanford University - Stanford University, Students, Stanford University - Stanford University, Students, Stanford Law School and Stanford University - Department of Computer Science
Downloads 2,315 (16,207)
Citation 10

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2.

AI Regulation Has Its Own Alignment Problem: The Technical and Institutional Feasibility of Disclosure, Registration, Licensing, and Auditing

George Washington Law Review, Forthcoming
Number of pages: 85 Posted: 30 Nov 2023 Last Revised: 31 Dec 2025
Neel Guha, Christie Lawrence, Lindsey A. Gailmard, Kit Rodolfa, Faiz Surani, Rishi Bommasani, Inioluwa Raji, Mariano-Florentino Cuéllar, Colleen Honigsberg, Percy Liang and Daniel E. Ho
Stanford University, Stanford University, Stanford University, Stanford University, University of California, Santa Barbara, Stanford University, affiliation not provided to SSRN, Carnegie Endowment for International Peace, Stanford Law School, Stanford University - Department of Computer Science and Stanford Law School
Downloads 1,515 (31,838)

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artificial intelligence regulation, regulation, artificial intelligence policy, technology policy, technology law

3.

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

Downloads 1,075 (53,108)
Citation 2

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

Stanford Public Law Working Paper
Number of pages: 30 Posted: 13 Jun 2025 Last Revised: 31 Oct 2025
A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Kevin Klyman, Matthew Jagielski, Katja Filippova, Ken Liu, Alexandra Chouldechova, Jamie Hayes, Eleni Triantafillou, Peter Kairouz, Nicole Mitchell, Niloofar Mireshghallah, Abigail Jacobs, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Ilia Shumailov, Andreas Terzis, Solon Barocas, Jennifer Wortman Vaughan, Danah Boyd, Yejin Choi, Sanmi Koyejo, Fernando Delgado, Percy Liang, Daniel E. Ho, Pamela Samuelson, Yangsibo Huang, Hanna Wallach, Miles Brundage, Amy Cyphert, David Bau, Mark A. Lemley, Seth Neel, Nicolas Papernot and Katherine Lee
Yale University, Google DeepMind, Independent, affiliation not provided to SSRN, Google DeepMind, Google DeepMind, Stanford University, Carnegie Mellon University - H. John Heinz III School of Public Policy and Management, Google DeepMind, Google DeepMind, Google Research, Google Research, University of Washington - Paul G. Allen School of Computer Science & Engineering, University of Michigan at Ann Arbor, Cornell Law School, Cornell University - Cornell Tech NYC, Cornell University - Department of Computer Science, Google DeepMind, Google DeepMind, Microsoft ResearchCornell University, Microsoft Research New York City, Microsoft Research, University of Washington, Stanford University, Cornell University, Stanford University - Department of Computer Science, Stanford University, University of California, Berkeley - School of Law, Google Research, Microsoft Research New York City, Independent, West Virginia University - College of Law, Northeastern Univeristy, Stanford Law School, University of Pennsylvania - Statistics Department, University of Toronto and Cornell University - Department of Computer Science
Downloads 561 (122,393)

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machine learning, generative AI, copyright, privacy, safety, machine unlearning

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

Yale Law & Economics Research Paper, Stanford Public Law Working Paper, WVU College of Law Research Paper No. 2025-004
Number of pages: 35 Posted: 06 Feb 2025 Last Revised: 14 Jun 2025
A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, Nicole Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, Amy Cyphert, Mark A. Lemley, Danah Boyd, Jennifer Wortman Vaughan, Miles Brundage, David Bau, Seth Neel, Abigail Jacobs, Andreas Terzis, Hanna Wallach, Nicolas Papernot and Katherine Lee
Yale University, Google DeepMind, Independent, Google DeepMind, Google DeepMind, Stanford University, Independent, Google DeepMind, Google Research, University of Washington - Paul G. Allen School of Computer Science & Engineering, Google DeepMind, Google DeepMind, Google Research, Google Research, Stanford University - Department of Computer Science, Stanford Law School, University of Washington, Stanford University, Cornell University, Cornell Law School, Cornell University - Cornell Tech NYC, Cornell University - Department of Computer Science, Microsoft ResearchCornell University, West Virginia University - College of Law, Stanford Law School, Microsoft Research, Microsoft Research New York City, Independent, Northeastern Univeristy, University of Pennsylvania - Statistics Department, University of Michigan at Ann Arbor, Google DeepMind, Microsoft Research New York City, University of Toronto and Cornell University - Department of Computer Science
Downloads 514 (140,772)
Citation 2

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machine unlearning, privacy, copyright, safety, Generative AI

4.

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

Stanford Public Law Working Paper, WVU College of Law Research Paper No. 2025-005
Number of pages: 187 Posted: 21 May 2025 Last Revised: 08 May 2026
A. Feder Cooper, Mark A. Lemley, Allison Casasola, Ahmed Ahmed, Aaron Gokaslan, Amy Cyphert, Christopher De Sa, Daniel E. Ho and Percy Liang
Yale University, Stanford Law School, Stanford, Stanford University, Cornell University - Cornell Tech NYC, West Virginia University - College of Law, Cornell University - Department of Computer Science, Stanford Law School and Stanford University - Department of Computer Science
Downloads 333 (226,528)
Citation 1

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AI, LLM, Large Language Models, Copyright

5.

Extracting Books from Production Language Models

Number of pages: 40 Posted: 12 Jan 2026
Ahmed Ahmed, A. Feder Cooper, Percy Liang and Sanmi Koyejo
Stanford University, Yale University, Stanford University - Department of Computer Science and Stanford University
Downloads 114 (630,858)

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6.

Bringing Machine Learning and Compositional Semantics Together

Annual Review of Linguistics, Vol. 1, Issue 1, pp. 355-376, 2015
Posted: 07 Aug 2015
Percy Liang and Christopher Potts
Stanford University - Department of Computer Science and Stanford University - Department of Linguistics

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