Simulating Real Users with State Alignment

The School of EECS is hosting the following UQ DS Research Seminar:

Simulating Real Users with State Alignment

Speaker: Evelyn Hejin Choi (Stanford)

Host: Ruihong Qiu

Coordinator: Dr Zijian Wang

Website: https://uq-ds-seminar.github.io/humanlm-evelyn/

Abstract: User simulation offers a scalable path toward more human-centered AI systems. However, current approaches largely rely on response imitation, capturing surface-level language patterns rather than the deeper user states, such as beliefs, emotions, and goals, that drive human behavior. In this talk, I will present HumanLM, a framework that aligns user simulators on deeper user states through reinforcement learning, outperforming supervised fine-tuning and RL baselines. Project page: https://humanlm.stanford.edu/

Speaker Bio: Evelyn Choi is a master’s student in Computer Science at Stanford University, where she received her B.S. in Computer Science. She works in Prof. James Zou’s lab, and her research interests include machine learning, NLP, and human-centered AI.