1 citations · 1 across the 8 of their papers we have counts for
4 papers · 1 filter
Autoregressive Diffusion World Models for Off-Policy Evaluation of LLM Agents
Kaixuan Liu, Guojun Xiong, Weinan Zhang +1
Evaluating large language model (LLM) agents in multi-turn interactive environments is expensive and risky, as it requires online environment interaction. We propose ADWM (Autoregr…
Social Networks of LLM Agents
Kaixuan Liu, Guojun Xiong, Weinan Zhang +1
Large language model (LLM) agents are increasingly deployed in interacting populations, raising the question of what such populations come to believe collectively. Whether a popula…
Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data
Lingkai Kong, Haichuan Wang, Tonghan Wang +2
Incorporating pre-collected offline data can substantially improve the sample efficiency of reinforcement learning (RL), but its benefits can break down when the transition dynamic…
Rule-Bottleneck Reinforcement Learning: Joint Explanation and Decision Optimization for Resource Allocation with Language Agents
Mauricio Tec, Guojun Xiong, Haichuan Wang +2
Deep Reinforcement Learning (RL) is remarkably effective in addressing sequential resource allocation problems in domains such as healthcare, public policy, and resource management…