AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity. - Silviu-Marian Udrescu; Andrew K. Tan; Jiahai Feng; Orisvaldo Neto; Tailin Wu; Max Tegmark (NeurIPS, 2020)

Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks. - Katherine M. Collins; Catherine Wong; Jiahai Feng; Megan Wei; Josh Tenenbaum 001 (CogSci, 2022)

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)

How do Language Models Bind Entities in Context? - Jiahai Feng; Jacob Steinhardt (ICLR, 2024)

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)

Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts. - Jiahai Feng; Stuart Russell 001; Jacob Steinhardt (CoRR, 2024)

Monitoring Latent World States in Language Models with Propositional Probes. - Jiahai Feng; Stuart Russell 001; Jacob Steinhardt (ICLR, 2025)