Participatory simulations of urban flooding for learning and decision support. - Jonathan M. Gilligan; Corey E. Brady; Janey V. Camp; John J. Nay; Pratim Sengupta (WSC, 2015)

Data-driven dynamic decision models. - John J. Nay; Jonathan M. Gilligan (WSC, 2015)

Gov2Vec: Learning Distributed Representations of Institutions and Their Legal Text. - John J. Nay (NLP+CSS@EMNLP, 2016)

Betting and belief: Prediction markets and attribution of climate change. - John J. Nay; Martin Van der Linden; Jonathan M. Gilligan (WSC, 2016)

Predicting and Understanding Law-Making with Machine Learning. - John J. Nay (CoRR, 2016)

Predicting Human Cooperation. - John J. Nay; Yevgeniy Vorobeychik (CoRR, 2016)

A Machine Learning Approach to Modeling Dynamic Decision-Making in Strategic Interactions and Prediction Markets. - John J. Nay (2017)

Law Informs Code: A Legal Informatics Approach to Aligning Artificial Intelligence with Humans. - John J. Nay (CoRR, 2022)

LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models. - 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; et al. (NeurIPS, 2023)

Large Language Models as Corporate Lobbyists. - John J. Nay (CoRR, 2023)

Large Language Models as Fiduciaries: A Case Study Toward Robustly Communicating With Artificial Intelligence Through Legal Standards. - John J. Nay (CoRR, 2023)

Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence. - John J. Nay; David Karamardian; Sarah B. Lawsky; Wenting Tao; Meghana Bhat; Raghav Jain; Aaron Travis Lee; Jonathan H. Choi; Jungo Kasai (CoRR, 2023)

ARB: Advanced Reasoning Benchmark for Large Language Models. - Tomohiro Sawada; Daniel Paleka; Alexander Havrilla; Pranav Tadepalli; Paula Vidas; Alexander Kranias; John J. Nay; Kshitij Gupta; Aran Komatsuzaki (CoRR, 2023)

LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models. - 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; et al. (CoRR, 2023)

Deception in Reinforced Autonomous Agents: The Unconventional Rabbit Hat Trick in Legislation. - Atharvan Dogra; Ameet Deshpande; John J. Nay; Tanmay Rajpurohit; Ashwin Kalyan; Balaraman Ravindran (CoRR, 2024)

Language Models can Subtly Deceive Without Lying: A Case Study on Strategic Phrasing in Legislation. - Atharvan Dogra; Krishna Pillutla; Ameet Deshpande; Ananya B. Sai; John J. Nay; Tanmay Rajpurohit; Ashwin Kalyan; Balaraman Ravindran (ACL (1), 2025)