CodaRAG improves RAG by using a CLS-inspired three-stage pipeline of knowledge consolidation, multi-dimensional associative navigation, and interference elimination, delivering 7-11% gains on GraphRAG-Bench for factual and reasoning tasks.
H.2 Stage II Retrieval and Stage III Post-Retrieval H.2.1 Query-related Cues Generation.Following LightRAG [ 6], we extract high-level and low-level keywords from the user query
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CodaRAG: Connecting the Dots with Associativity Inspired by Complementary Learning
CodaRAG improves RAG by using a CLS-inspired three-stage pipeline of knowledge consolidation, multi-dimensional associative navigation, and interference elimination, delivering 7-11% gains on GraphRAG-Bench for factual and reasoning tasks.