MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding. - Steven H. Wang; Antoine Scardigli; Leonard Tang; Wei Chen; Dimitry Levkin; Anya Chen; Spencer Ball; Thomas Woodside; Oliver Zhang; Dan Hendrycks (EMNLP, 2023)

Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the Machiavelli Benchmark. - Alexander Pan; Jun Shern Chan; Andy Zou; Nathaniel Li; Steven Basart; Thomas Woodside; Hanlin Zhang 002; Scott Emmons; Dan Hendrycks (ICML, 2023)

Artificial Influence: An Analysis Of AI-Driven Persuasion. - Matthew Burtell; Thomas Woodside (CoRR, 2023)

Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark. - Alexander Pan; Jun Shern Chan; Andy Zou; Nathaniel Li; Steven Basart; Thomas Woodside; Jonathan Ng; Hanlin Zhang 002; Scott Emmons; Dan Hendrycks (CoRR, 2023)

An Overview of Catastrophic AI Risks. - Dan Hendrycks; Mantas Mazeika; Thomas Woodside (CoRR, 2023)

Responsible Reporting for Frontier AI Development. - Noam Kolt; Markus Anderljung; Joslyn Barnhart; Asher Brass; Kevin Esvelt; Gillian K. Hadfield; Lennart Heim; Mikel Rodriguez; Jonas B. Sandbrink; Thomas Woodside (AIES (1), 2024)