Learning adaptive planning representations with natural language guidance. - Lionel Wong; Jiayuan Mao; Pratyusha Sharma; Zachary S. Siegel; Jiahai Feng; Noa Korneev; Joshua B. Tenenbaum; Jacob Andreas (CoRR, 2023)

Learning Grounded Action Abstractions from Language. - Lionel Wong; Jiayuan Mao; Pratyusha Sharma; Zachary S. Siegel; Jiahai Feng; Noa Korneev; Joshua B. Tenenbaum; Jacob Andreas (ICLR, 2024)

CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark. - Zachary S. Siegel; Sayash Kapoor; Nitya Nagdir; Benedikt Stroebl; Arvind Narayanan (CoRR, 2024)

CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark. - Zachary S. Siegel; Sayash Kapoor; Nitya Nadgir; Benedikt Stroebl; Arvind Narayanan (Trans. Mach. Learn. Res., 2024)

SGD with Weight Decay Secretly Minimizes the Ranks of Your Neural Networks. - Tomer Galanti; Zachary S. Siegel; Aparna Gupte; Tomaso A. Poggio (CPAL, 2025)

BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval. - Hongjin Su; Howard Yen; Mengzhou Xia; Weijia Shi; Niklas Muennighoff; Han-yu Wang; Haisu Liu; Quan Shi; Zachary S. Siegel; Michael Tang; Ruoxi Sun 002; Jinsung Yoon; et al. (ICLR, 2025)

AI Agents That Matter. - Sayash Kapoor; Benedikt Stroebl; Zachary S. Siegel; Nitya Nadgir; Arvind Narayanan (Trans. Mach. Learn. Res., 2025)