AI RESEARCH
M-RAG: Making RAG Faster, Stronger, and More Efficient
arXiv CS.AI
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ArXi:2603.26667v1 Announce Type: cross Retrieval-Augmented Generation (RAG) has become a widely adopted paradigm for enhancing the reliability of large language models (LLMs). However, RAG systems are sensitive to retrieval strategies that rely on text chunking to construct retrieval units, which often