Empirical Analysis and Detection of Hallucinations in LLM-Generated Bug Report Summaries 事件

Empirical Analysis and Detection of Hallucinations in LLM-Generated Bug Report Summaries arXiv:2605.24137v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to generate summaries of software bug reports, including sections such as Steps-to-Reproduce (S2R), Actual Behavior (AB), and Expected Behavior (EB). However, these models frequently produce hallucinations that can be convincing but unsupported by the source report. This can mislead developers and reduce tru