AI RESEARCH
TaSR-RAG: Taxonomy-guided Structured Reasoning for Retrieval-Augmented Generation
arXiv CS.AI
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ArXi:2603.09341v1 Announce Type: cross Retrieval-Augmented Generation (RAG) helps large language models (LLMs) answer knowledge-intensive and time-sensitive questions by conditioning generation on external evidence. However, most RAG systems still retrieve unstructured chunks and rely on one-shot generation, which often yields redundant context, low information density, and brittle multi-hop reasoning.