Peter Henderson
Orcid: 0000-0003-3938-0541Affiliations:
- Stanford University, CA, USA
- McGill University, Montreal, QC, Canada (former)
According to our database1,
Peter Henderson
authored at least 55 papers
between 2015 and 2024.
Collaborative distances:
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Bibliography
2024
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications.
CoRR, 2024
Rethinking Machine Learning Benchmarks in the Context of Professional Codes of Conduct.
Proceedings of the Symposium on Computer Science and Law, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!
CoRR, 2023
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models.
CoRR, 2023
CoRR, 2023
Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
CoRR, 2022
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022
Proceedings of the 2022 Symposium on Computer Science and Law, 2022
2021
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset.
CoRR, 2021
CoRR, 2021
When does pretraining help?: assessing self-supervised learning for law and the CaseHOLD dataset of 53, 000+ legal holdings.
Proceedings of the ICAIL '21: Eighteenth International Conference for Artificial Intelligence and Law, São Paulo Brazil, June 21, 2021
TDprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning?
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021
2020
Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop.
CoRR, 2020
CoRR, 2020
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning.
CoRR, 2020
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020
2019
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version.
Dialogue Discourse, 2018
Distilling Information from a Flood: A Possibility for the Use of Meta-Analysis and Systematic Review in Machine Learning Research.
CoRR, 2018
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods.
CoRR, 2018
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018
Proceedings of the 2nd Annual Conference on Robot Learning, 2018
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
OptionGAN: Learning Joint Reward-Policy Options Using Generative Adversarial Inverse Reinforcement Learning.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control.
CoRR, 2017
CoRR, 2017
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017
2016
2015