Understanding and Mitigating Hallucination Escape in Tool-Using LLM Agents

Excerpt

arXiv:2610.04409v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly serve as autonomous agents that invoke external tools. However, this capability introduces tool hallucination, selecting incorrect tools or generating invalid calls. Existing mitigation methods report substantial improvements, yet we identify a previously overlooked failure mode that we term Hallucination Escape. These methods reduce hallucination on the tool configuration they are tuned on but increase i