2 papers
cs.CL2026
HumanLM: Simulating Users with State Alignment Beats Response Imitation
Shirley Wu, Evelyn Choi, Arpandeep Khatua +7
Large Language Models (LLMs) are increasingly used to simulate how specific users respond to a given context, enabling more user-centric applications that rely on user feedback. Ho…
cs.LG2025
Reinforcement Learning for Machine Learning Engineering Agents
Sherry Yang, Joy He-Yueya, Percy Liang
Existing agents for solving tasks such as ML engineering rely on prompting powerful language models. As a result, these agents do not improve with more experience. In this paper, w…