Catching AI Tool-Use Hallucinations in Real Time
AI agents powered by large language models can call tools, but they also hallucinate: picking the wrong tool, sending malformed parameters, or bypassing tools by simulating results. That breaks reliability, security, and audit trails in production.
This study shows a lightweight way to catch those mistakes in real time. Instead of extra checks or multiple runs, it taps the model's own internal representations during the same forward pass to flag risky tool choices and parameter errors.
- Up to 86.4% detection accuracy across reasoning tasks, with minimal overhead.
- Excels at parameter-level hallucinations and wrong-tool selection.
- Enables early fallback: safer defaults, retries, or human review.
By Kait Healy, Bharathi Srinivasan, Visakh Madathil, and Jing Wu. Paper: https://arxiv.org/abs/2601.05214v1
Paper: https://arxiv.org/abs/2601.05214v1
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