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cs.CL2026
Beyond Chunk-Local Extraction: Cross-Chunk Graph Augmentation for GraphRAG
Jiaming Zhang, Yibo Zhao, Jing Yu +2
GraphRAG extends retrieval-augmented generation by organizing corpora as explicit knowledge graphs, enabling graph-based retrieval for complex question answering. However, existing…
cs.CL2026
LLM-Specific Utility for Retrieval-Augmented Generation
Hengran Zhang, Keping Bi, Jiafeng Guo +4
Retrieval-augmented generation (RAG) is typically optimized for topical relevance, yet its success ultimately depends on whether retrieved passages are useful for a large language…