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EAR: Entity-Aware Partitioning Approach for Retrieval-Augmented Generation Development
Retrieval-augmented generation (RAG) can improve knowledge-intensive question answering, but the first design choice is easy to overlook: how should the source corpus be partitioned into retrievable units? Fixed-size chunks often return long passages whose relation to the question is only implicit.
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