AcCoRD: Evaluating User-Agent Collaboration Under Realistic User Preference Dynamics
arXiv cs.AIen
arXiv cs.AI
AI Global WirearXiv:2608.27818v1 Announce Type: new Abstract: User preferences in user-agent collaboration are rarely static and fully-specified upfront: preferences are formed, revealed, adjusted, and relaxed during interaction. Existing benchmarks for evaluating user-agent collaboration focus almost exclusively on resolving underspecified preferences, thereby failing to capture the richer dynamics of real-world interaction. We introduce AcCoRD, a user-agent collaboration benchmark requiring agents to handle diverse user preference dynamics in two domains: online shopping and travel planning. We evaluate five frontier LLMs under two prompting strategies: vanilla ReAct, and an uncertainty-guided variant t
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