VitaBench 2.0: Evaluating Personalized and Proactive Agents in Long-Term User Interactions 事件

VitaBench 2.0: Evaluating Personalized and Proactive Agents in Long-Term User Interactions arXiv:2605.27141v1 Announce Type: new Abstract: Large language models (LLMs) have evolved into interactive agents that collaborate with users in real-world tasks. Effective collaboration in such settings increasingly depends on understanding the user beyond what is explicitly stated, as user intent is often reflected in fragmented daily interactions and requires both personalized modeling and proactive in