ToolSearcher: Optimizing Tool Selection at Scale via Reinforcement Learning
This work proposes ToolSearcher, a novel RL framework for effective multi-turn search and fine-grained optimization in large-scale tool selection, which introduces category-constrained tool discrimination to improve the model's ability to distinguish functionally similar tools.
Zhen-Long Dai, Xu-Jie Song, Zi-Tong Wang et al.
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