Do LLM s Catch Their Own Mistakes? A Comprehensive Benchmark for Reflective Tool Use LLM s
Zheyuan Liu · Liqiang Xiao · Yang Li · Hyokun Yun · Lihong Li · Chao Zhang · Meng Jiang
摘要
Large language models (LLMs) increasingly rely on external tools to complete complex tasks, yet their ability to recognize and correct their own tool-use mistakes remains underexplored. Existing benchmarks primarily evaluate planning and execution success, overlooking the self-reflective dimensio...