2 citations · 4 across the 11 of their papers we have counts for
6 papers · 1 filter
GoodPoint: Learning Constructive Scientific Paper Feedback from Author Responses
Jimin Mun, Chani Jung, Xuhui Zhou +2
While LLMs hold significant potential to transform scientific research, we advocate for their use to augment and empower researchers rather than to automate research without human…
Social World Models
Xuhui Zhou, Jiarui Liu, Akhila Yerukola +2
Humans intuitively navigate social interactions by simulating unspoken dynamics and reasoning about others' perspectives, even with limited information. In contrast, AI systems str…
1-2-3 Check: Enhancing Contextual Privacy in LLM via Multi-Agent Reasoning
Wenkai Li, Liwen Sun, Zhenxiang Guan +2
Addressing contextual privacy concerns remains challenging in interactive settings where large language models (LLMs) process information from multiple sources (e.g., summarizing m…
HAICOSYSTEM: An Ecosystem for Sandboxing Safety Risks in Human-AI Interactions
Xuhui Zhou, Hyunwoo Kim, Faeze Brahman +9
AI agents are increasingly autonomous in their interactions with human users and tools, leading to increased interactional safety risks. We present HAICOSYSTEM, a framework examini…
AI-LieDar: Examine the Trade-off Between Utility and Truthfulness in LLM Agents
Zhe Su, Xuhui Zhou, Sanketh Rangreji +4
Truthfulness (adherence to factual accuracy) and utility (satisfying human needs and instructions) are both fundamental aspects of Large Language Models, yet these goals often conf…
On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents
Jen-tse Huang, Jiaxu Zhou, Tailin Jin +6
Large language model-based multi-agent systems have shown great abilities across various tasks due to the collaboration of expert agents, each focusing on a specific domain. Howeve…