CalBench
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CalBench: Evaluating Coordination-Privacy Trade-offs in Multi-Agent LLMs
arXiv:2605.09823v3 Announce Type: replace Abstract: Personal AI assistants are beginning to act as delegates with access to calendars, inboxes, and user preferences. Calendar scheduling makes the trust problem concrete: an assistant must coordinate with other assistants while deciding what to reveal about the person it represents. We introduce CalBench, a controlled benchmark for multi-agent calendar scheduling under private information.