What In-Context Learning "Learns" In-Context: Disentangling Task Recognition and Task Learning. - Jane Pan; Tianyu Gao 001; Howard Chen 003; Danqi Chen 001 (ACL (Findings), 2023)

bayesassurance: An R Package for Calculating Sample Size and Bayesian Assurance. - Jane Pan; Sudipto Banerjee (R J., 2023)

Spontaneous Reward Hacking in Iterative Self-Refinement. - Jane Pan; He He 001; Samuel R. Bowman; Shi Feng 005 (CoRR, 2024)

When Benchmarks Talk: Re-Evaluating Code LLMs with Interactive Feedback. - Jane Pan; Ryan Shar; Jacob Pfau; Ameet Talwalkar; He He 001; Valerie Chen (ACL (Findings), 2025)

Reasoning Models Know When They're Right: Probing Hidden States for Self-Verification. - Anqi Zhang; Yulin Chen; Jane Pan; Chen Zhao; Aurojit Panda; Jinyang Li; He He 001 (CoRR, 2025)

Beyond Memorization: Mapping the Originality-Quality Frontier of Language Models. - Vishakh Padmakumar; Chen Yueh-Han; Jane Pan; Valerie Chen; He He 001 (CoRR, 2025)