2 citations · 7 across the 17 of their papers we have counts for
4 papers · 1 filter
Mitigating Context Interference for Reliable and Efficient Search Agents
Boyang Xue, Bin Wu, Shuofei Qiao +8
Recent research empowers Large Language Models (LLMs) as multi-turn search agents to iteratively retrieve and generate outputs until complex tasks are solved. However, the contexts…
UXBench: Benchmarking User Experience in AI Assistants
Mengze Hong, Xia Zeng, Zeyang Lei +27
As AI assistants serve millions of users daily, evaluating user experience (UX) beyond general model capability has become increasingly important. We present \textbf{UXBench}, the…
TherapyGym: Evaluating and Aligning Clinical Fidelity and Safety in Therapy Chatbots
Fangrui Huang, Souhad Chbeir, Arpandeep Khatua +8
Large language models (LLMs) are increasingly used for mental-health support; yet prevailing evaluation methods--fluency metrics, preference tests, and generic dialogue benchmarks-…
ToolSelf: Unifying Task Execution and Self-Reconfiguration via Tool-Driven Emergent Adaptation
Jingqi Zhou, Sheng Wang, Dezhao Deng +9
LLM-powered agentic systems excel at complex long-horizon tasks, but remain constrained by static configurations fixed before execution. Such rigidity forces a trade-off between do…