32 citations · 111 across the 39 of their papers we have counts for
43 papers
When Does Retrieval Help? A Study of In-Context Adaptation in Vision-Language-Action Models
Zixuan Liu, Joris Köster, Zizhan Zheng +1
Vision-language-action (VLA) models have shown strong potential as generalist robot policies, but adapting them to unseen tasks often requires costly parameter updates. Recent work…
Adaptive Multilevel Twisted Sequential Monte Carlo for Rare Events Estimation in Language Models
Zixuan Liu, Fangzheng Wu, Brian Summa +1
Rare unsafe behaviors in large language models can remain practically significant even when their probability is extremely small, particularly at deployment scales involving millio…
Robust General Utility for Reinforcement Learning
Zixuan Liu, Fangzheng Wu, Brian Summa +1
Reinforcement learning (RL) with general utility extends classic RL by optimizing an arbitrary utility functional of the policy-induced occupancy measure, thereby enabling a broade…
Stealthy World Model Manipulation via Data Poisoning
Yibin Hu, Xiaolin Sun, Zizhan Zheng
Model-based learning agents use learned world models to predict future states, plan actions, and adapt to new environments. However, the process of updating world models from colle…
Insider Attacks in Multi-Agent LLM Consensus Systems
Xiaolin Sun, Zixuan Liu, Yibin Hu +1
Large language models (LLMs) are increasingly deployed in multi-agent systems where agents communicate in natural language to solve tasks jointly. A key capability in such systems…
Robust Optimization for Mitigating Reward Hacking with Correlated Proxies
Zixuan Liu, Xiaolin Sun, Zizhan Zheng
Designing robust reinforcement learning (RL) agents in the presence of imperfect reward signals remains a core challenge. In practice, agents are often trained with proxy rewards t…