Publications

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, An Adversarial Perspective on Machine Unlearning for AI Safety, arXiv preprint (2024).

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, Fantastic Copyrighted Beasts and How (Not) to Generate Them, GenLaw Workshop (ICML) (2024).

PDF Spotlight @ GenLaw Workshop (ICML 2024)

, Evaluating Copyright Takedown Methods for Language Models, NeurIPS Datasets & Benchmarks and GenLaw Workshop @ ICML (2024).

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, Corpus Enigmas and Contradictory Linguistics: Tensions between Empirical Semantic Meaning and Judicial Interpretation, Minnesota Journal of Law, Science & Technology (2024).

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, What’s in Your Safe Data?: Identifying Benign Data that Breaks Safety, Conference on Language Modeling (2024).

PDF Best Paper Award @ Data Problems for Foundation Models Workshop (ICLR 2024)

, Beyond Open vs. Closed: Emerging Consensus and Key Questions for Foundation AI Model Governance, Carnegie Endowment for International Peace (2024).

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, Rethinking Machine Learning Benchmarks in the Context of Professional Codes of Conduct, Proceedings of the Symposium on Computer Science and Law (2024).

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, Promises and Pitfalls of Artificial Intelligence for Legal Applications, Journal of Cross-disciplinary Research in Computational Law (2024).

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, On the Societal Impact of Open Foundation Models, International Conference on Machine Learning (2024).

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, A Safe Harbor for AI Evaluation and Red Teaming, International Conference on Machine Learning (2024).

PDF Oral Presentation @ ICML 2024

, AI Risk Management Should Incorporate Both Safety and Security, arXiv preprint arXiv:2405.19524 (2024).

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, Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications, International Conference on Machine Learning (2024).

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, Visual adversarial examples jailbreak aligned large language models, Proceedings of the AAAI Conference on Artificial Intelligence (2024).

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, SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal Behaviors, arXiv preprint (2024).

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, Safety Alignment Should Be Made More Than Just a Few Tokens Deep, arXiv preprint arXiv:2406.05946 (2024).

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, Liability for AI-generated Speech, Oxford Handbook on the Foundations and Regulation of Generative AI (2024, forthcoming) (2024).

, Challenges for Foundation Model Liability and Regulatory Regimes: An Analysis of US Law, Cambridge Handbook on Generative AI and the Law (2024, forthcoming) (2024).

, Brief Of Law Scholars As Amici Curiae In Support Of Defendant’S Cross-Motion For Summary Judgment And In Opposition To Plaintiffs’ Motion For Summary Judgment, Bristol Myers Squibb Company V. Xavier Becerra, Janssen Pharmaceuticals V. Xavier Becerra (2023).

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, Brief Of Amici Curiae Professors Of Tax Law, Legal History, And Computational Science In Support Of Respondent, Moore v. United States (2023).

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, Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!, arXiv Preprint (2023).

PDF Code Press (VentureBeat) Press (The Register) Press (NYTimes)

, LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models, NeurIPS Datasets & Benchmarks Track (2023).

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, Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs, NeurIPS (2023).

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, Algorithmic Rulemaking v. Algorithmic Guidance, Harvard Journal of Law and Technology (2023).

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, Where's the liability in harmful AI speech?, Journal of Free Speech Law (2023).

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, Freedom of Speech and AI Output, Journal of Free Speech Law (2023).

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, Self-Destructing Models: Increasing the Costs of Harmful Dual Uses in Foundation Models, AAAI/ACM Conference on AI, Ethics, and Society (2023).

PDF Code Honorable Mention for Best Student Paper

, Holistic Evaluation of Language Models, Transactions on Machine Learning Research (2023).

PDF Code Website HAI Blog Press (VentureBeat)

, Should the United States or the European Union Follow China’s Lead and Require Watermarks for Generative AI?, Georgetown Journal of International Affairs (2023).

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, Foundation Models and Fair Use, Journal of Machine Learning Research (2023).

PDF HAI Blog Jotwell Review by Pamela Samuelson Press Mention (New York Times) Press Mention (Planet Money)

, Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection, AAAI Conference on Artificial Intelligence (AAAI), Adaptive Experimental Design and Active Learning in the Real World (ReALML@ICML) (non-archival), and 12th Annual IRS/TPC Joint Research Conference on Tax Administration (non-archival) (2023).

PDF Video Spotlight Talk, ReALML@ICML Press (Reuters)

, Entropy Regularization for Population Estimation, AAAI Conference on Artificial Intelligence (AAAI) (2023).

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, Text Characterization Toolkit, The 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Demo Track) (2022).

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, BLOOM: A 176B-Parameter Open-Access Multilingual Language Model, arXiv Preprint (2022).

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, Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset, NeurIPS Datasets & Benchmarks Track (2022).

PDF Code Featured Paper @ NeurIPS '22 HAI Blog Press (Bloomberg Law) Press (FiveThirtyEight)

, Vulnerabilities in Discovery Tech, Harvard Journal of Law and Technology (2022).

PDF Dataset Website Jotwell (Mention as part of coverage for another piece)

, Data Governance in the Age of Large-Scale Data-Driven Language Technology, ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) (2022).

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, Beyond Ads: Sequential Decision-Making Algorithms in Law and Public Policy, 2nd ACM Symposium on Computer Science and Law and Causal Inference Challenges in Sequential Decision Making: Bridging Theory and Practice, a NeurIPS 2021 Workshop (2022).

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, On the Opportunities and Risks of Foundation Models, (2021).

PDF Website Press (VentureBeat) Press (Forbes) Press (Discover Magazine)

, When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset, International Conference on Artificial Intelligence and Law (ICAIL) (2021).

PDF Code Carole Hafner Best Paper Award at ICAIL 2021

, How US law will evaluate artificial intelligence for covid-19, BMJ (2021).

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, TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?, Theoretical Foundations of RL Workshop and Beyond First order methods in ML Systems Workshop (ICML), 2020 and 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS) (2021).

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, Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning, Journal of Machine Learning Research (2020).

PDF Code HAI Blog Press (WSJ, mention) Inspired Microsoft Azure's Carbon Metrics Used by SustainNLP 2020 Shared Task

, An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning, Biological and Artificial Reinforcement Learning Workshop (NeurIPS) (2020).

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, With Little Power Comes Great Responsibility, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020).

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, Prioritizing Public Health Resources for COVID-19 Investigations: How Administrative Data Can Protect Vulnerable Populations, Health Affairs Blog (2020).

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, Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies: Law Enforcement at Customs and Border Protection, Report Submitted to the Administrative Conference of the United States (2020).

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, Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims, (2020).

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, Separating value functions across time-scales, International Conference on Machine Learning (ICML) and The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM) (2019).

PDF Code Oral Presentation

, Distilling Information from a Flood: A Possibility for the Use of Meta-Analysis and Systematic Review in Machine Learning Research, Critiquing and Correcting Trends in Machine Learning Workshop (CRACT) at NeurIPS (2018).

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, The RLLChatbot: a solution to the ConvAI challenge, arXiv preprint arXiv:1811.02714 (2018).

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, An Introduction to Deep Reinforcement Learning, Foundations and Trends in Machine Learning (2018).

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, Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods, The 14th European Workshop on Reinforcement Learning (EWRL 2018) (2018).

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, Reward Estimation for Variance Reduction in Deep Reinforcement Learning, Proceedings of The 2nd Conference on Robot Learning (2018).

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, Cost Adaptation for Robust Decentralized Swarm Behaviour, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2018).

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, Adversarial Gain, arXiv preprint arXiv:1811.01302 (2018).

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, Reproducibility and Reusability in Deep Reinforcement Learning, M.Sc. Thesis. McGill University (2018).

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, Oríon: Experiment Version Control for Efficient Hyperparameter Optimization, Reproducibility in Machine Learning Workshop (ICML) (2018).

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, OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning, AAAI Conference on Artificial Intelligence (AAAI) (2018).

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, Ethical Challenges in Data-Driven Dialogue Systems, AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) (2018).

PDF Code Oral Presentation

, Deep Reinforcement Learning that Matters, AAAI Conference on Artificial Intelligence (AAAI) (2018).

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, Reward Estimation for Variance Reduction in Deep Reinforcement Learning, International Conference on Learning Representations Workshop (ICLR) (2018).

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, A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version, Dialogue & Discourse (2018).

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, Learning Robust Dialog Policies in Noisy Environments, Conversational AI Workshop (NeurIPS) (2017).

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, Bayesian Policy Gradients via Alpha Divergence Dropout Inference, Bayesian Deep Learning Workshop (NeurIPS) (2017).

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, Underwater Multi-Robot Convoying using Visual Tracking by Detection, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2017).

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, Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control, Reproducibility in Machine Learning Workshop (ICML) (2017).

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, Benchmark Environments for Multitask Learning in Continuous Domains, Lifelong Learning: A Reinforcement Learning Approach Workshop (ICML) (2017).

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, An Analysis of Parallelized Motion Masking Using Dual-Mode Single Gaussian Models, arXiv preprint arXiv:1702.05156 (2017).

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, Chaotic Memory Randomization for Securing Embedded Systems, arXiv preprint arXiv:1611.00742 (2016).

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, Implanted intracortical electrodes as chronic neural interfaces to the central nervous system, PeerJ PrePrints (2015).

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