Papers with multi-turn agent-to-agent conversations

1 papers
ConVerse: Benchmarking Contextual Safety in Agent-to-Agent Conversations (2026.findings-eacl)

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Challenge: Large language models (LLMs) are rapidly transitioning from passive text generators to autonomous agents that act and communicate on behalf of users.
Approach: a new benchmark evaluates privacy and security risks in agent–agent interactions . a converse model enables attackers to embed malicious requests within plausible discourse . the model is based on a three-tier taxonomy assessing abstraction quality .
Outcome: ConVerse tests privacy and security risks in agent–agent interactions with 12 user personas and over 864 contextually grounded attacks.

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