Adversarial training for high-stakes reliability. - Daniel M. Ziegler; Seraphina Nix; Lawrence Chan; Tim Bauman; Peter Schmidt-Nielsen; Tao Lin 014; Adam Scherlis; Noa Nabeshima; Ben Weinstein-Raun; Daniel de Haas; Buck Shlegeris; Nate Thomas (NeurIPS, 2022)

Evaluating Language-Model Agents on Realistic Autonomous Tasks. - Megan Kinniment; Lucas Jun Koba Sato; Haoxing Du; Brian Goodrich; Max Hasin; Lawrence Chan; Luke Harold Miles; Tao Roa Lin; Hjalmar Wijk; Joel Burget; Aaron Ho; Elizabeth Barnes; et al. (CoRR, 2023)

RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts. - Hjalmar Wijk; Tao Lin 014; Joel Becker; Sami Jawhar; Neev Parikh; Thomas Broadley; Lawrence Chan; Michael Chen; Joshua Clymer; Jai Dhyani; Elena Ericheva; Katharyn Garcia; et al. (CoRR, 2024)

Measuring AI Ability to Complete Long Tasks. - Thomas Kwa; Ben West; Joel Becker; Amy Deng; Katharyn Garcia; Max Hasin; Sami Jawhar; Megan Kinniment; Nate Rush; Sydney von Arx; Ryan Bloom; Thomas Broadley; et al. (CoRR, 2025)