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F$^{2}$DR: A Fine-Grained Full-Pipeline Reward Framework for DeepSearch Workflows
With the widespread industrial deployment of Large Language Models (LLMs), DeepSearch has emerged as the dominant paradigm for resolving complex user queries. It typically operates through an iterative closed-loop workflow consisting of planning and reflection, information retrieval, and answer gene
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