Henderson, Peter

On the Opportunities and Risks of Foundation Models

Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 2,676

Deep Reinforcement Learning That Matters

Henderson, P., Islam, R., Bachman, P., Pineau, J., Precup, D., & Meger, D. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Reinforcement Learning in RoboticsScientific Computing and Data Management

Cited by 1,685

An introduction to deep reinforcement learning

François-Lavet, V., Henderson, P., Islam, R., Bellemare, M. G., & Pineau, J. (2018) · now publishers, Inc. eBooks

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 544

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

Henderson, P., Hu, J., Romoff, J., Brunskill, E., Jurafsky, D., & Pineau, J. (2020) · arXiv

Green IT and SustainabilityEnergy Efficiency in Computing

Cited by 393

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims

Brundage, M., Avin, S., Wang, J., Belfield, H., Krueger, G., Hadfield, G., Khlaaf, H., Yang, J., Toner, H., Fong, R., et al. (2020) · arXiv

Ethics and Social Impacts of AISafety Systems Engineering in Autonomy

Cited by 306

Holistic Evaluation of Language Models

Liang, P., Bommasani, R., Lee, T., Tsipras, D., Soylu, D., Yasunaga, M., Zhang, Y., Narayanan, D., Wu, Y., Kumar, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 255

Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control

Islam, R., Henderson, P., Gomrokchi, M., & Precup, D. (2017) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 177

Legalbench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

Guha, N., Nyarko, J., Ho, D. E., Ré, C., Chilton, A., Narayana, A., Chohlas-Wood, A., Peters, A., Waldon, B., Rockmore, D., et al. (2023) · SSRN Electronic Journal

Artificial Intelligence in LawTopic Modeling

Cited by 154

Visual Adversarial Examples Jailbreak Aligned Large Language Models

Qi, X., Huang, K., Panda, A., Henderson, P., Wang, M., & Mittal, P. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 150

On the Societal Impact of Open Foundation Models

Kapoor, S., Bommasani, R., Klyman, K., Longpre, S., Ramaswami, A., Cihon, P., Hopkins, A., Bankston, K., Biderman, S., Bogen, M., et al. (2024) · arXiv

Ethics and Social Impacts of AILaw, AI, and Intellectual Property

Cited by 103

With Little Power Comes Great Responsibility

Card, D., Henderson, P., Khandelwal, U., Jia, R., Mahowald, K., & Jurafsky, D. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Natural Language Processing TechniquesTopic Modeling

Cited by 84

Data Governance in the Age of Large-Scale Data-Driven Language Technology

Jernite, Y., Nguyen, H., Biderman, S., Rogers, A., Masoud, M., Danchev, V., Tan, S., Luccioni, A. S., Subramani, N., Johnson, I., et al. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 75

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

Henderson, P., Krass, M., Zheng, L., Guha, N., Manning, C. D., Jurafsky, D., & Ho, D. (2022) · Advances in Neural Information Processing Systems 35

Artificial Intelligence in LawEthics and Social Impacts of AI

Cited by 62

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

Henderson, P., Krass, M. S., Zheng, L., Guha, N., Manning, C. D., Jurafsky, D., & Ho, D. E. (2022) · arXiv

Artificial Intelligence in LawEthics and Social Impacts of AI

Cited by 49

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

Guha, N., Nyarko, J., Ho, D. E., Ré, C., Chilton, A., Narayana, A., Chohlas-Wood, A., Peters, A., Waldon, B., Rockmore, D. N., et al. (2023) · arXiv

Artificial Intelligence in LawTopic Modeling

Cited by 30

Promises and Pitfalls of Artificial Intelligence for Legal Applications

Kapoor, S., Henderson, P., & Narayanan, A. (2024) · SSRN Electronic Journal

Artificial Intelligence in LawArtificial Intelligence Applications

Cited by 25

Promises and pitfalls of artificial intelligence for legal applications

Kapoor, S., Henderson, P., & Narayanan, A. (2024) · arXiv

Artificial Intelligence in LawArtificial Intelligence Applications

Cited by 25

Open technical problems in open-weight ai model risk management

Casper, S., O'Brien, K., Longpre, S., Seger, E., Klyman, K., Bommasani, R., Nrusimha, A., Shumailov, I., Mindermann, S., Basart, S., et al. (2025) · SSRN Electronic Journal

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 3

LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?

Zheng, Z., Cheng, Z., Shen, Z., Zhou, S., Liu, K., He, H., Li, D., Wei, S., Hao, H., Yao, J., et al. (2025) · arXiv

Teaching and Learning ProgrammingSoftware Engineering Research

Cited by 1

Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation

Kapoor, S., Stroebl, B., Kirgis, P., Nadgir, N., Siegel, Z. S., Wei, B., Xue, T., Chen, Z., Chen, F., Utpala, S., et al. (2025) · arXiv

Artificial Intelligence ApplicationsAI-based Problem Solving and Planning

Cited by 0