Papers with LLM-driven proxy user

1 papers
Communication-Efficient Desire Alignment for Proactive Embodied Human–Agent Interaction (2026.acl-long)

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Challenge: Effective real-world human–agent interactions are long-term and repeated.
Approach: They propose a simulation that uses a proxy user with value-driven preferences and natural language behavior to evaluate how agents adapt to users across interactions and satisfy their desires.
Outcome: HA-Desire, a home assistance simulation, shows that agents can adapt to user needs and provide proactive assistance within limited communication.

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