1 citations · 1 across the 12 of their papers we have counts for
13 papers
Social Gym and SPaRTan: Benchmarking and Improving LLM Social Reasoning via Multi-Agent Game Tournaments
Keyu He, Xuhui Zhou, Maarten Sap
LLM agents are increasingly deployed in multi-agent social settings where they must cooperate, negotiate, and adapt to other agents. Measuring and improving these social skills is…
OdysSim: Building Foundation Models for Human Behavior Simulation
Xuhui Zhou, Weiwei Sun, Weihua Du +6
Large language models are increasingly deployed as human simulators for interactive evaluation and social simulation. Yet helpfulness-driven post-training pulls them toward a homog…
Reinforcing Human Behavior Simulation via Verbal Feedback
Weiwei Sun, Xuhui Zhou, Jiarui Liu +13
Humans learn social norms and behaviors from verbal feedback (e.g., a parent saying "that was rude" or a friend explaining "here's why that hurt"). Yet, learning from feedback for…
CodeScout: An Effective Recipe for Reinforcement Learning of Code Search Agents
Lintang Sutawika, Aditya Bharat Soni, Bharath Sriraam R R +8
A prerequisite for coding agents to perform tasks on large repositories is code localization - the identification of relevant files, classes, and functions to work on. While reposi…
Mind the Sim2Real Gap in User Simulation for Agentic Tasks
Xuhui Zhou, Weiwei Sun, Qianou Ma +8
As NLP evaluation shifts from static benchmarks to multi-turn interactive settings, LLM-based simulators have become widely used as user proxies, serving two roles: generating user…
The OpenHands Software Agent SDK: A Composable and Extensible Foundation for Production Agents
Xingyao Wang, Simon Rosenberg, Juan Michelini +8
Agents are now used widely in the process of software development, but building production-ready software engineering agents is a complex task. Deploying software agents effectivel…
Training Proactive and Personalized LLM Agents
Weiwei Sun, Xuhui Zhou, Weihua Du +5
Despite rapid progress, current AI agents are primarily optimized for isolated task completion. We argue for a paradigm shift toward training agents as collaborators that communica…
TOM-SWE: User Mental Modeling For Software Engineering Agents
Xuhui Zhou, Valerie Chen, Zora Zhiruo Wang +3
Recent advances in coding agents have made them capable of planning, editing, running, and testing complex code bases. Despite their growing ability in coding tasks, these systems…
How can we assess human-agent interactions? Case studies in software agent design
Valerie Chen, Rohit Malhotra, Xingyao Wang +7
While benchmarks measure the accuracy of LLM-powered agents, they mostly assume full automation, failing to represent the collaborative nature of real-world use cases. In this pape…
OpenAgentSafety: A Comprehensive Framework for Evaluating Real-World AI Agent Safety
Sanidhya Vijayvargiya, Aditya Bharat Soni, Xuhui Zhou +4
Recent advances in AI agents capable of solving complex, everyday tasks, from scheduling to customer service, have enabled deployment in real-world settings, but their possibilitie…
Ambig-SWE: Interactive Agents to Overcome Underspecificity in Software Engineering
Sanidhya Vijayvargiya, Xuhui Zhou, Akhila Yerukola +2
AI agents are increasingly being deployed to automate tasks, often based on underspecified user instructions. Making unwarranted assumptions to compensate for the missing informati…
AutoPresent: Designing Structured Visuals from Scratch
Jiaxin Ge, Zora Zhiruo Wang, Xuhui Zhou +8
Designing structured visuals such as presentation slides is essential for communicative needs, necessitating both content creation and visual planning skills. In this work, we tack…
TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks
Frank F. Xu, Yufan Song, Boxuan Li +18
We interact with computers on an everyday basis, be it in everyday life or work, and many aspects of work can be done entirely with access to a computer and the Internet. At the sa…