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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.
Dynamic Uncertainty with Noisy Correspondences (DUNC), a novel framework that incorporates two key components that incorporates Cross-modal Evidential Learning (CEL), which models bidirectional alignment uncertainty using a Dirichlet distribution to capture the confidence in image–text similarity, and Dynamic Robust Lo...
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