HCAST: Human-Calibrated Autonomy Software Tasks

1 code implementation • 21 Mar 2025 • David Rein, Joel Becker, Amy Deng, Seraphina Nix, Chris Canal, Daniel O'Connel, Pip Arnott, Ryan Bloom, Thomas Broadley, Katharyn Garcia, Brian Goodrich, Max Hasin, Sami Jawhar, Megan Kinniment, Thomas Kwa, Aron Lajko, Nate Rush, Lucas Jun Koba Sato, Sydney von Arx, Ben West, Lawrence Chan, Elizabeth Barnes

To understand and predict the societal impacts of highly autonomous AI systems, we need benchmarks with grounding, i. e., metrics that directly connect AI performance to real-world effects we care about.

Measuring AI Ability to Complete Long Tasks

1 code implementation • 18 Mar 2025 • 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, Haoxing Du, Brian Goodrich, Nikola Jurkovic, Luke Harold Miles, Seraphina Nix, Tao Lin, Neev Parikh, David Rein, Lucas Jun Koba Sato, Hjalmar Wijk, Daniel M. Ziegler, Elizabeth Barnes, Lawrence Chan

Despite rapid progress on AI benchmarks, the real-world meaning of benchmark performance remains unclear.

Logical Reasoning

RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts

2 code implementations • 22 Nov 2024 • Hjalmar Wijk, Tao Lin, Joel Becker, Sami Jawhar, Neev Parikh, Thomas Broadley, Lawrence Chan, Michael Chen, Josh Clymer, Jai Dhyani, Elena Ericheva, Katharyn Garcia, Brian Goodrich, Nikola Jurkovic, Megan Kinniment, Aron Lajko, Seraphina Nix, Lucas Sato, William Saunders, Maksym Taran, Ben West, Elizabeth Barnes

We confirm that our experts make progress in the environments given 8 hours, with 82% of expert attempts achieving a non-zero score and 24% matching or exceeding our strong reference solutions.

AI Agent Language Modeling +1