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Paper · arXiv

ToolRACER: A Robust Agentic Conversation Emulation Resource for Agent Training and Evaluation

Task-oriented conversational agents remain fragile under real world conversation scenarios as they rarely follow a predictable script, especially when users exhibit non-cooperative behavior. Existing function-calling benchmarks often emphasize successful, cooperative interactions and underrepresent adversarial conversation trajectories, thereby limiting the training resources available for developing robust agents. We present ToolRACER, a synthetic data generation pipeline that coordinates user, assistant and tool emulation models to generate and validated multi-turn interactions between a user and an agent. Using \sysn, we construct ToolRACERBench a robust multi-turn conversation benchma...

AuthorsArkajyoti Chakraborty, Aryan Tayal, Ishika Agarwal et al.
Primary categorycs.CL
Published6 October 2026
Last updated at source6 October 2026
cs.CLcs.AI
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