default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDPeter Henderson 0002
Person information
- affiliation: Princeton University, Center For Information Technology Policy, NJ, USA
- affiliation (former, PhD 2023): Stanford University, CA, USA
- affiliation (former): McGill University, Montreal, QC, Canada
Other persons with the same name
- Peter Henderson 0001 — University of Southampton, School of Electronics and Computer Science, UK (and 1 more)
Other persons with a similar name
- Peter B. Henderson — Butler University, Indianapolis, Department of Computer Science and Software Engineering, USA
SPARQL queries 
🛈 Please note that only 58% of the items listed on this page have a DOI stored with their dblp record. Therefore, DOI-based queries can only provide partial results.
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
showing all ?? records
2020 – today
- 2026
[j8]Stephen Casper, Kyle O'Brien, Shayne Longpre, Elizabeth Seger, Kevin Klyman, Rishi Bommasani, Aniruddha Nrusimha, Ilia Shumailov, Sören Mindermann, Steven Basart, Frank Rudzicz, Kellin Pelrine, Avijit Ghosh, Andrew Strait, Robert Kirk, Dan Hendrycks, Peter Henderson, J. Zico Kolter, Geoffrey Irving, Yarin Gal, Yoshua Bengio, Dylan Hadfield-Menell:
Open Technical Problems in Open-Weight AI Model Risk Management. Trans. Mach. Learn. Res. 2026 (2026)- [j7]Noam Kolt, Nicholas Caputo, Jack Boeglin, Cullen O'Keefe, Rishi Bommasani, Stephen Casper, Mariano-Florentino Cuellar, Noah Feldman, Iason Gabriel, Gillian K. Hadfield, Lewis Hammond, Peter Henderson, Atoosa Kasirzadeh, Seth Lazar, Anka Reuel, Kevin Wei, Jonathan Zittrain:
Legal Alignment for Safe and Ethical AI. Trans. Mach. Learn. Res. 2026 (2026) - [c36]Kylie Zhang, Nimra Nadeem, Lucia Zheng, Dominik Stammbach
, Peter Henderson:
AI-Assisted Moot Courts: Simulating Justice-Specific Questioning in Oral Arguments. CSLAW 2026: 136-172 - [i78]Noam Kolt, Nicholas Caputo, Jack Boeglin, Cullen O'Keefe, Rishi Bommasani, Stephen Casper, Mariano-Florentino Cuellar, Noah Feldman, Iason Gabriel, Gillian K. Hadfield, Lewis Hammond, Peter Henderson, Atoosa Kasirzadeh, Seth Lazar, Anka Reuel, Kevin Wei, Jonathan Zittrain:
Legal Alignment for Safe and Ethical AI. CoRR abs/2601.04175 (2026) - [i77]Dominik Stammbach, Kylie Zhang, Patty Liu, Nimra Nadeem, Lucia Zheng, Peter Henderson:
Legal Retrieval for Public Defenders. CoRR abs/2601.14348 (2026) - [i76]Kylie Zhang, Nimra Nadeem, Lucia Zheng, Dominik Stammbach, Peter Henderson:
AI-Assisted Moot Courts: Simulating Justice-Specific Questioning in Oral Arguments. CoRR abs/2603.04718 (2026) - [i75]Hadas Orgad, Boyi Wei, Kaden Zheng, Martin Wattenberg, Peter Henderson, Seraphina Goldfarb-Tarrant, Yonatan Belinkov:
Large Language Models Generate Harmful Content Using a Distinct, Unified Mechanism. CoRR abs/2604.09544 (2026) - [i74]Zeyu Shen, Peter Henderson:
Temporally Extended Mixture-of-Experts Models. CoRR abs/2604.20156 (2026) - 2025
- [j6]Jakub Lucki, Boyi Wei, Yangsibo Huang, Peter Henderson, Florian Tramèr, Javier Rando:
An Adversarial Perspective on Machine Unlearning for AI Safety. Trans. Mach. Learn. Res. 2025 (2025) - [c35]Lucia Zheng, Neel Guha, Javokhir Arifov, Sarah Zhang, Michal Skreta, Christopher D. Manning, Peter Henderson, Daniel E. Ho:
A Reasoning-Focused Legal Retrieval Benchmark. CSLAW 2025: 169-193 - [c34]Sibo Ma, Alejandro Salinas, Julian Nyarko, Peter Henderson:
Breaking Down Bias: On The Limits of Generalizable Pruning Strategies. FAccT 2025: 2437-2450 - [c33]Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson:
Fantastic Copyrighted Beasts and How (Not) to Generate Them. ICLR 2025 - [c32]Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, Xiao Ma, Subhrajit Roy, Ahmad Beirami, Prateek Mittal, Peter Henderson:
Safety Alignment Should be Made More Than Just a Few Tokens Deep. ICLR 2025 - [c31]Xiangyu Qi, Boyi Wei, Nicholas Carlini, Yangsibo Huang, Tinghao Xie, Luxi He, Matthew Jagielski, Milad Nasr, Prateek Mittal, Peter Henderson:
On Evaluating the Durability of Safeguards for Open-Weight LLMs. ICLR 2025 - [c30]Tinghao Xie, Xiangyu Qi, Yi Zeng, Yangsibo Huang, Udari Madhushani Sehwag, Kaixuan Huang, Luxi He, Boyi Wei, Dacheng Li, Ying Sheng, Ruoxi Jia, Bo Li, Kai Li, Danqi Chen, Peter Henderson, Prateek Mittal:
SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal. ICLR 2025 - [c29]Shayne Longpre, Kevin Klyman, Ruth Elisabeth Appel, Sayash Kapoor, Rishi Bommasani, Michelle Sahar, Sean McGregor, Avijit Ghosh, Borhane Blili-Hamelin, Nathan Butters, Alondra Nelson, Amit Elazari, Andrew Sellars, Casey John Ellis, Dane Sherrets, Dawn Song, Harley Geiger, Ilona Cohen, Lauren McIlvenny, Madhulika Srikumar, Mark M. Jaycox, Markus Anderljung, Nadine Farid Johnson, Nicholas Carlini, Nicolas Miailhe, Nik Marda, Peter Henderson, Rebecca S. Portnoff, Rebecca Weiss, Victoria Westerhoff, Yacine Jernite, Rumman Chowdhury, Percy Liang, Arvind Narayanan:
Position: In-House Evaluation Is Not Enough. Towards Robust Third-Party Evaluation and Flaw Disclosure for General-Purpose AI. ICML (Position Papers) 2025 - [c28]Joel Niklaus, Lucia Zheng, Arya D. McCarthy, Christopher Hahn, Brian M. Rosen, Peter Henderson, Daniel E. Ho, Garrett Honke, Percy Liang, Christopher D. Manning:
LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain. NAACL (Findings) 2025: 127-152 - [i73]Sibo Ma, Alejandro Salinas, Peter Henderson, Julian Nyarko:
Breaking Down Bias: On The Limits of Generalizable Pruning Strategies. CoRR abs/2502.07771 (2025) - [i72]Faiz Surani, Mirac Suzgun, Vyoma Raman, Christopher D. Manning, Peter Henderson, Daniel E. Ho:
AI for Scaling Legal Reform: Mapping and Redacting Racial Covenants in Santa Clara County. CoRR abs/2503.03888 (2025) - [i71]Lexin Zhou, Lorenzo Pacchiardi, Fernando Martínez-Plumed, Katherine M. Collins, Yael Moros-Daval, Seraphina Zhang, Qinlin Zhao, Yitian Huang, Luning Sun, Jonathan E. Prunty, Zongqian Li, Pablo Sánchez-García, Kexin Jiang Chen, Pablo A. M. Casares, Jiyun Zu, John Burden, Behzad Mehrbakhsh, David Stillwell, Manuel Cebrián, Jindong Wang, Peter Henderson, Sherry Tongshuang Wu, Patrick C. Kyllonen, Lucy Cheke, Xing Xie, José Hernández-Orallo:
General Scales Unlock AI Evaluation with Explanatory and Predictive Power. CoRR abs/2503.06378 (2025) - [i70]Luxi He, Xiangyu Qi, Michel Liao, Inyoung Cheong, Prateek Mittal, Danqi Chen, Peter Henderson:
The Deployment of End-to-End Audio Language Models Should Take into Account the Principle of Least Privilege. CoRR abs/2503.16833 (2025) - [i69]Shayne Longpre, Kevin Klyman, Ruth E. Appel, Sayash Kapoor, Rishi Bommasani, Michelle Sahar, Sean McGregor, Avijit Ghosh, Borhane Blili-Hamelin, Nathan Butters, Alondra Nelson, Amit Elazari, Andrew Sellars, Casey John Ellis, Dane Sherrets, Dawn Song, Harley Geiger, Ilona Cohen, Lauren McIlvenny, Madhulika Srikumar, Mark M. Jaycox, Markus Anderljung, Nadine Farid Johnson, Nicholas Carlini, Nicolas Miailhe, Nik Marda, Peter Henderson, Rebecca S. Portnoff, Rebecca Weiss, Victoria Westerhoff, Yacine Jernite, Rumman Chowdhury, Percy Liang, Arvind Narayanan:
In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI. CoRR abs/2503.16861 (2025) - [i68]Lucia Zheng, Neel Guha, Javokhir Arifov, Sarah Zhang, Michal Skreta, Christopher D. Manning, Peter Henderson, Daniel E. Ho:
A Reasoning-Focused Legal Retrieval Benchmark. CoRR abs/2505.03970 (2025) - [i67]Boyi Wei, Benedikt Stroebl, Jiacen Xu, Joie Zhang, Zhou Li, Peter Henderson:
Dynamic Risk Assessments for Offensive Cybersecurity Agents. CoRR abs/2505.18384 (2025) - [i66]Zihan Zheng, Zerui Cheng, Zeyu Shen, Shang Zhou, Kaiyuan Liu, Hansen He, Dongruixuan Li, Stanley Wei, Hangyi Hao, Jianzhu Yao, Peiyao Sheng, Zixuan Wang, Wenhao Chai, Aleksandra Korolova, Peter Henderson, Sanjeev Arora, Pramod Viswanath, Jingbo Shang, Saining Xie:
LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming? CoRR abs/2506.11928 (2025) - [i65]Inyoung Cheong, Alicia Guo, Mina Lee, Zhehui Liao, Kowe Kadoma, Dongyoung Go, Joseph Chee Chang, Peter Henderson, Mor Naaman, Amy X. Zhang:
Penalizing Transparency? How AI Disclosure and Author Demographics Shape Human and AI Judgments About Writing. CoRR abs/2507.01418 (2025) - [i64]Luxi He, Nimra Nadeem, Michel Liao, Howard Chen, Danqi Chen, Mariano-Florentino Cuellar, Peter Henderson:
Statutory Construction and Interpretation for Artificial Intelligence. CoRR abs/2509.01186 (2025) - [i63]Sayash Kapoor, Benedikt Stroebl, Peter Kirgis, Nitya Nadgir, Zachary S. Siegel, Boyi Wei, Tianci Xue, Ziru Chen, Felix Chen, Saiteja Utpala, Franck Ndzomga, Dheeraj Oruganty, Sophie Luskin, Kangheng Liu, Botao Yu, Amit Arora, Dongyoon Hahm, Harsh Trivedi, Huan Sun, Juyong Lee, Tengjun Jin, Yifan Mai, Yifei Zhou, Yuxuan Zhu, Rishi Bommasani, Daniel Kang, Dawn Song, Peter Henderson, Yu Su, Percy Liang, Arvind Narayanan:
Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation. CoRR abs/2510.11977 (2025) - [i62]Shang Zhou, Zihan Zheng, Kaiyuan Liu, Zeyu Shen, Zerui Cheng, Zexing Chen, Hansen He, Jianzhu Yao, Huanzhi Mao, Qiuyang Mang, Tianfu Fu, Beichen Li, Dongruixuan Li, Wenhao Chai, Zhuang Liu, Aleksandra Korolova, Peter Henderson, Natasha Jaques, Pramod Viswanath, Saining Xie, Jingbo Shang:
AutoCode: LLMs as Problem Setters for Competitive Programming. CoRR abs/2510.12803 (2025) - [i61]Gaku Morio, Harri Rowlands, Dominik Stammbach, Christopher D. Manning, Peter Henderson:
A Multimodal Benchmark for Framing of Oil & Gas Advertising and Potential Greenwashing Detection. CoRR abs/2510.21679 (2025) - [i60]Inyoung Cheong, Patty Liu, Dominik Stammbach, Peter Henderson:
How Can AI Augment Access to Justice? Public Defenders' Perspectives on AI Adoption. CoRR abs/2510.22933 (2025) - [i59]Boyi Wei, Zora Che, Nathaniel Li, Udari Madhushani Sehwag, Jasper Götting, Samira Nedungadi, Julian Michael, Summer Yue, Dan Hendrycks, Peter Henderson, Zifan Wang, Seth Donoughe, Mantas Mazeika:
Best Practices for Biorisk Evaluations on Open-Weight Bio-Foundation Models. CoRR abs/2510.27629 (2025) - [i58]Qiuyang Mang, Wenhao Chai, Zhifei Li, Huanzhi Mao, Shang Zhou, Alexander Du, Hanchen Li, Shu Liu, Edwin Chen, Yichuan Wang, Xieting Chu, Zerui Cheng, Yuan Xu, Tian Xia, Zirui Wang, Tianneng Shi, Jianzhu Yao, Yilong Zhao, Qizheng Zhang, Charlie Ruan, Zeyu Shen, Kaiyuan Liu, Runyuan He, Dong Xing, Zerui Li, Zirong Zeng, Yige Jiang, Lufeng Cheng, Ziyi Zhao, Youran Sun, Wesley Zheng, Meiyuwang Zhang, Ruyi Ji, Xuechang Tu, Zihan Zheng, Zexing Chen, Kangyang Zhou, Zhaozi Wang, Jingbang Chen, Aleksandra Korolova, Peter Henderson, Pramod Viswanath, Vijay Ganesh, Saining Xie, Zhuang Liu, Dawn Song, Sewon Min, Ion Stoica, Joseph E. Gonzalez, Jingbo Shang, Alvin Cheung:
FrontierCS: Evolving Challenges for Evolving Intelligence. CoRR abs/2512.15699 (2025) - 2024
- [j5]Shayne Longpre, Stella Biderman, Alon Albalak, Hailey Schoelkopf, Daniel McDuff, Sayash Kapoor, Kevin Klyman, Kyle Lo, Gabriel Ilharco, Nay San, Maribeth Rauh, Aviya Skowron, Bertie Vidgen, Laura Weidinger, Arvind Narayanan, Victor Sanh, David Ifeoluwa Adelani, Percy Liang, Rishi Bommasani, Peter Henderson, Sasha Luccioni, Yacine Jernite, Luca Soldaini:
The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources. Trans. Mach. Learn. Res. 2024 (2024) - [c27]Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Peter Henderson, Mengdi Wang, Prateek Mittal:
Visual Adversarial Examples Jailbreak Aligned Large Language Models. AAAI 2024: 21527-21536 - [c26]Peter Henderson, Jieru Hu, Mona T. Diab, Joelle Pineau:
Rethinking Machine Learning Benchmarks in the Context of Professional Codes of Conduct. CSLAW 2024: 109-120 - [c25]Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson:
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! ICLR 2024 - [c24]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:
Position: On the Societal Impact of Open Foundation Models. ICML 2024: 23082-23104 - [c23]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
Position: A Safe Harbor for AI Evaluation and Red Teaming. ICML 2024: 32691-32710 - [c22]Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson:
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. ICML 2024: 52588-52610 - [c21]Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, Peter Henderson:
Evaluating Copyright Takedown Methods for Language Models. NeurIPS 2024 - [i57]Sayash Kapoor, Peter Henderson, Arvind Narayanan:
Promises and pitfalls of artificial intelligence for legal applications. CoRR abs/2402.01656 (2024) - [i56]Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson:
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. CoRR abs/2402.05162 (2024) - [i55]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
A Safe Harbor for AI Evaluation and Red Teaming. CoRR abs/2403.04893 (2024) - [i54]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:
On the Societal Impact of Open Foundation Models. CoRR abs/2403.07918 (2024) - [i53]Luxi He, Mengzhou Xia, Peter Henderson:
What's in Your "Safe" Data?: Identifying Benign Data that Breaks Safety. CoRR abs/2404.01099 (2024) - [i52]Joel Niklaus, Lucia Zheng, Arya D. McCarthy, Christopher Hahn, Brian M. Rosen, Peter Henderson, Daniel E. Ho, Garrett Honke, Percy Liang, Christopher D. Manning:
FLawN-T5: An Empirical Examination of Effective Instruction-Tuning Data Mixtures for Legal Reasoning. CoRR abs/2404.02127 (2024) - [i51]Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J. Su, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal:
AI Risk Management Should Incorporate Both Safety and Security. CoRR abs/2405.19524 (2024) - [i50]Minzhou Pan, Yi Zeng, Xue Lin, Ning Yu, Cho-Jui Hsieh, Peter Henderson, Ruoxi Jia:
JIGMARK: A Black-Box Approach for Enhancing Image Watermarks against Diffusion Model Edits. CoRR abs/2406.03720 (2024) - [i49]Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, Xiao Ma, Subhrajit Roy, Ahmad Beirami, Prateek Mittal, Peter Henderson:
Safety Alignment Should Be Made More Than Just a Few Tokens Deep. CoRR abs/2406.05946 (2024) - [i48]Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson:
Fantastic Copyrighted Beasts and How (Not) to Generate Them. CoRR abs/2406.14526 (2024) - [i47]Tinghao Xie, Xiangyu Qi, Yi Zeng, Yangsibo Huang, Udari Madhushani Sehwag, Kaixuan Huang, Luxi He, Boyi Wei, Dacheng Li, Ying Sheng, Ruoxi Jia, Bo Li, Kai Li, Danqi Chen, Peter Henderson, Prateek Mittal:
SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal Behaviors. CoRR abs/2406.14598 (2024) - [i46]Shayne Longpre, Stella Biderman, Alon Albalak, Hailey Schoelkopf, Daniel McDuff, Sayash Kapoor, Kevin Klyman, Kyle Lo, Gabriel Ilharco, Nay San, Maribeth Rauh, Aviya Skowron, Bertie Vidgen, Laura Weidinger, Arvind Narayanan, Victor Sanh, David Ifeoluwa Adelani, Percy Liang, Rishi Bommasani, Peter Henderson, Sasha Luccioni, Yacine Jernite, Luca Soldaini:
The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources. CoRR abs/2406.16746 (2024) - [i45]Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, Peter Henderson:
Evaluating Copyright Takedown Methods for Language Models. CoRR abs/2406.18664 (2024) - [i44]Jakub Lucki, Boyi Wei, Yangsibo Huang, Peter Henderson, Florian Tramèr, Javier Rando:
An Adversarial Perspective on Machine Unlearning for AI Safety. CoRR abs/2409.18025 (2024) - [i43]Peter Henderson, Mark A. Lemley:
The Mirage of Artificial Intelligence Terms of Use Restrictions. CoRR abs/2412.07066 (2024) - [i42]Xiangyu Qi, Boyi Wei, Nicholas Carlini, Yangsibo Huang, Tinghao Xie, Luxi He, Matthew Jagielski, Milad Nasr, Prateek Mittal, Peter Henderson:
On Evaluating the Durability of Safeguards for Open-Weight LLMs. CoRR abs/2412.07097 (2024) - 2023
- [j4]Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang:
Foundation Models and Fair Use. J. Mach. Learn. Res. 24: 400:1-400:79 (2023) - [j3]Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda:
Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 2023 (2023) - [c20]Peter Henderson, Ben Chugg, Brandon R. Anderson, Kristen M. Altenburger, Alex Turk, John Guyton, Jacob Goldin, Daniel E. Ho:
Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection. AAAI 2023: 5087-5095 - [c19]Ben Chugg, Peter Henderson, Jacob Goldin, Daniel E. Ho:
Entropy Regularization for Population Estimation. AAAI 2023: 12198-12204 - [c18]Peter Henderson, Eric Mitchell, Christopher D. Manning, Dan Jurafsky, Chelsea Finn:
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models. AIES 2023: 287-296 - [c17]Neel Guha, Julian Nyarko, Daniel E. Ho, Christopher Ré, Adam Chilton, K. Aditya, 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:
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models. NeurIPS 2023 - [c16]Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang:
Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models. NeurIPS 2023 - [i41]Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang:
Foundation Models and Fair Use. CoRR abs/2303.15715 (2023) - [i40]Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang:
Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs. CoRR abs/2305.02440 (2023) - [i39]Peter Henderson, Tatsunori Hashimoto, Mark A. Lemley:
Where's the Liability in Harmful AI Speech? CoRR abs/2308.04635 (2023) - [i38]Eugene Volokh, Mark A. Lemley, Peter Henderson:
Freedom of Speech and AI Output. CoRR abs/2308.08673 (2023) - [i37]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:
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models. CoRR abs/2308.11462 (2023) - [i36]Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson:
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! CoRR abs/2310.03693 (2023) - 2022
- [c15]Peter Henderson, Ben Chugg, Brandon R. Anderson, Daniel E. Ho:
Beyond Ads: Sequential Decision-Making Algorithms in Law and Public Policy. CSLAW 2022: 87-100 - [c14]Yacine Jernite, Huu Nguyen, Stella Biderman, Anna Rogers, Maraim Masoud, Valentin Danchev, Samson Tan, Alexandra Sasha Luccioni, Nishant Subramani, Isaac Johnson, Gérard Dupont, Jesse Dodge, Kyle Lo, Zeerak Talat, Dragomir R. Radev, Aaron Gokaslan, Somaieh Nikpoor, Peter Henderson, Rishi Bommasani, Margaret Mitchell:
Data Governance in the Age of Large-Scale Data-Driven Language Technology. FAccT 2022: 2206-2222 - [c13]Daniel Simig, Tianlu Wang, Verna Dankers, Peter Henderson, Khuyagbaatar Batsuren, Dieuwke Hupkes, Mona T. Diab:
Text Characterization Toolkit (TCT). AACL/IJCNLP (System Demonstrations) 2022: 72-87 - [c12]Peter Henderson, Mark S. Krass, Lucia Zheng, Neel Guha, Christopher D. Manning, Dan Jurafsky, Daniel E. Ho:
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. NeurIPS 2022 - [i35]Peter Henderson, Ben Chugg, Brandon R. Anderson, Kristen M. Altenburger, Alex Turk, John Guyton, Jacob Goldin, Daniel E. Ho:
Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection. CoRR abs/2204.11910 (2022) - [i34]Yacine Jernite, Huu Nguyen, Stella Biderman, Anna Rogers, Maraim Masoud, Valentin Danchev, Samson Tan, Alexandra Sasha Luccioni, Nishant Subramani, Gérard Dupont, Jesse Dodge, Kyle Lo, Zeerak Talat, Isaac Johnson, Dragomir R. Radev, Somaieh Nikpoor, Jörg Frohberg, Aaron Gokaslan, Peter Henderson, Rishi Bommasani, Margaret Mitchell:
Data Governance in the Age of Large-Scale Data-Driven Language Technology. CoRR abs/2206.03216 (2022) - [i33]Peter Henderson, Mark S. Krass, Lucia Zheng, Neel Guha, Christopher D. Manning, Dan Jurafsky, Daniel E. Ho:
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. CoRR abs/2207.00220 (2022) - [i32]Ben Chugg, Peter Henderson, Jacob Goldin, Daniel E. Ho:
Entropy Regularization for Population Estimation. CoRR abs/2208.11747 (2022) - [i31]Daniel Simig, Tianlu Wang, Verna Dankers, Peter Henderson, Khuyagbaatar Batsuren, Dieuwke Hupkes, Mona T. Diab:
Text Characterization Toolkit. CoRR abs/2210.01734 (2022) - [i30]Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda:
Holistic Evaluation of Language Models. CoRR abs/2211.09110 (2022) - [i29]Eric Mitchell, Peter Henderson, Christopher D. Manning, Dan Jurafsky, Chelsea Finn:
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses in Foundation Models. CoRR abs/2211.14946 (2022) - 2021
- [c11]Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau:
TDprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning? AAMAS 2021: 1082-1090 - [c10]Lucia Zheng, Neel Guha, Brandon R. Anderson, Peter Henderson, Daniel E. Ho:
When does pretraining help?: assessing self-supervised learning for law and the CaseHOLD dataset of 53, 000+ legal holdings. ICAIL 2021: 159-168 - [i28]Dilip Arumugam, Peter Henderson, Pierre-Luc Bacon:
An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning. CoRR abs/2103.06224 (2021) - [i27]Lucia Zheng, Neel Guha, Brandon R. Anderson, Peter Henderson, Daniel E. Ho:
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset. CoRR abs/2104.08671 (2021) - [i26]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 S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren E. 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 S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.:
On the Opportunities and Risks of Foundation Models. CoRR abs/2108.07258 (2021) - [i25]Peter Henderson, Ben Chugg, Brandon R. Anderson, Daniel E. Ho:
Beyond Ads: Sequential Decision-Making Algorithms in Public Policy. CoRR abs/2112.06833 (2021) - 2020
- [c9]Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky:
With Little Power Comes Great Responsibility. EMNLP (1) 2020: 9263-9274 - [i24]Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau:
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning. CoRR abs/2002.05651 (2020) - [i23]Miles Brundage, Shahar Avin, Jasmine Wang, Haydn Belfield, Gretchen Krueger, Gillian K. Hadfield, Heidy Khlaaf, Jingying Yang, Helen Toner, Ruth Fong, Tegan Maharaj, Pang Wei Koh, Sara Hooker, Jade Leung, Andrew Trask, Emma Bluemke, Jonathan Lebensold, Cullen O'Keefe, Mark Koren, Théo Ryffel, J. B. Rubinovitz, Tamay Besiroglu, Federica Carugati, Jack Clark, Peter Eckersley, Sarah de Haas, Maritza Johnson, Ben Laurie, Alex Ingerman, Igor Krawczuk, Amanda Askell, Rosario Cammarota, Andrew Lohn, David Krueger, Charlotte Stix, Peter Henderson, Logan Graham, Carina Prunkl, Bianca Martin, Elizabeth Seger, Noa Zilberman, Seán Ó hÉigeartaigh, Frens Kroeger, Girish Sastry, Rebecca Kagan, Adrian Weller, Brian Tse, Elizabeth Barnes, Allan Dafoe, Paul Scharre, Ariel Herbert-Voss, Martijn Rasser, Shagun Sodhani, Carrick Flynn, Thomas Krendl Gilbert, Lisa Dyer, Saif M. Khan, Yoshua Bengio, Markus Anderljung:
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. CoRR abs/2004.07213 (2020) - [i22]Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau:
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning? CoRR abs/2007.02786 (2020) - [i21]Shagun Sodhani, Mayoore S. Jaiswal, Lauren Baker, Koustuv Sinha, Carl Shneider, Peter Henderson, Joel Lehman, Ryan Lowe:
Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop. CoRR abs/2007.10546 (2020) - [i20]Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky:
With Little Power Comes Great Responsibility. CoRR abs/2010.06595 (2020)
2010 – 2019
- 2019
- [c8]Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Joelle Pineau, Emma Brunskill:
Separable value functions across time-scales. ICML 2019: 5468-5477 - [i19]Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Emma Brunskill, Joelle Pineau:
Separating value functions across time-scales. CoRR abs/1902.01883 (2019) - 2018
- [j2]Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau:
A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version. Dialogue Discourse 9(1): 1-49 (2018) - [j1]Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau:
An Introduction to Deep Reinforcement Learning. Found. Trends Mach. Learn. 11(3-4): 219-354 (2018) - [c7]Peter Henderson, Wei-Di Chang, Pierre-Luc Bacon, David Meger, Joelle Pineau, Doina Precup:
OptionGAN: Learning Joint Reward-Policy Options Using Generative Adversarial Inverse Reinforcement Learning. AAAI 2018: 3199-3206 - [c6]Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger:
Deep Reinforcement Learning That Matters. AAAI 2018: 3207-3214 - [c5]Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau:
Ethical Challenges in Data-Driven Dialogue Systems. AIES 2018: 123-129 - [c4]Joshua Romoff, Peter Henderson, Alexandre Piché, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRL 2018: 674-699 - [c3]Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. ICLR (Workshop) 2018 - [c2]Peter Henderson, Matthew Vertescher, David Meger, Mark Coates:
Cost Adaptation for Robust Decentralized Swarm Behaviour. IROS 2018: 4099-4106 - [i18]Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRR abs/1805.03359 (2018) - [i17]Peter Henderson, Joshua Romoff, Joelle Pineau:
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods. CoRR abs/1810.02525 (2018) - [i16]Peter Henderson, Koustuv Sinha, Nan Rosemary Ke, Joelle Pineau:
Adversarial Gain. CoRR abs/1811.01302 (2018) - [i15]Nicolas Gontier, Koustuv Sinha, Peter Henderson, Iulian Serban, Michael Noseworthy, Prasanna Parthasarathi, Joelle Pineau:
The RLLChatbot: a solution to the ConvAI challenge. CoRR abs/1811.02714 (2018) - [i14]Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau:
An Introduction to Deep Reinforcement Learning. CoRR abs/1811.12560 (2018) - [i13]Peter Henderson, Emma Brunskill:
Distilling Information from a Flood: A Possibility for the Use of Meta-Analysis and Systematic Review in Machine Learning Research. CoRR abs/1812.01074 (2018) - 2017
- [c1]Florian Shkurti, Wei-Di Chang, Peter Henderson, Md Jahidul Islam, Juan Camilo Gamboa Higuera, Jimmy Li, Travis Manderson, Anqi Xu, Gregory Dudek, Junaed Sattar:
Underwater multi-robot convoying using visual tracking by detection. IROS 2017: 4189-4196 - [i12]Peter Henderson, Matthew Vertescher:
An Analysis of Parallelized Motion Masking Using Dual-Mode Single Gaussian Models. CoRR abs/1702.05156 (2017) - [i11]Riashat Islam, Peter Henderson, Maziar Gomrokchi, Doina Precup:
Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control. CoRR abs/1708.04133 (2017) - [i10]Peter Henderson, Wei-Di Chang, Florian Shkurti, Johanna Hansen, David Meger, Gregory Dudek:
Benchmark Environments for Multitask Learning in Continuous Domains. CoRR abs/1708.04352 (2017) - [i9]Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger:
Deep Reinforcement Learning that Matters. CoRR abs/1709.06560 (2017) - [i8]Peter Henderson, Wei-Di Chang, Pierre-Luc Bacon, David Meger, Joelle Pineau, Doina Precup:
OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning. CoRR abs/1709.06683 (2017) - [i7]Peter Henderson, Matthew Vertescher, David Meger, Mark Coates:
Cost Adaptation for Robust Decentralized Swarm Behaviour. CoRR abs/1709.07114 (2017) - [i6]Florian Shkurti, Wei-Di Chang, Peter Henderson, Md Jahidul Islam, Juan Camilo Gamboa Higuera, Jimmy Li, Travis Manderson, Anqi Xu, Gregory Dudek, Junaed Sattar:
Underwater Multi-Robot Convoying using Visual Tracking by Detection. CoRR abs/1709.08292 (2017) - [i5]Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau:
Ethical Challenges in Data-Driven Dialogue Systems. CoRR abs/1711.09050 (2017) - [i4]Peter Henderson, Thang Doan, Riashat Islam, David Meger:
Bayesian Policy Gradients via Alpha Divergence Dropout Inference. CoRR abs/1712.02037 (2017) - [i3]Maryam Fazel-Zarandi, Shang-Wen Li, Jin Cao, Jared Casale, Peter Henderson, David Whitney, Alborz Geramifard:
Learning Robust Dialog Policies in Noisy Environments. CoRR abs/1712.04034 (2017) - 2016
- [i2]Peter Henderson, Muthucumaru Maheswaran:
Chaotic Memory Randomization for Securing Embedded Systems. CoRR abs/1611.00742 (2016) - 2015
- [i1]Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau:
A Survey of Available Corpora for Building Data-Driven Dialogue Systems. CoRR abs/1512.05742 (2015)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2026-06-12 21:20 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
