How Can Input Reformulation Improve Tool Usage Accuracy in a Complex Dynamic Environment? A Study on tau-bench (2025.findings-emnlp)
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Venkatesh Mishra, Amir Saeidi, Satyam Raj, Mutsumi Nakamura, Gaowen Liu, Ali Payani, Jayanth Srinivasa, Chitta Baral
| Challenge: | Recent advances in reasoning and planning capabilities of large language models have enabled their potential as autonomous agents capable of tool use in dynamic environments. |
| Approach: | They propose an input-reformulation multi-agent framework that reformulates user queries . |
| Outcome: | The proposed framework outperforms ReAct, Function Calling, and Self-Reflection in overall pass5 scores. |
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