DOTRAG: Retrieval-Time Reasoning Along Paths

arXiv:2605.18760v2 Announce Type: replace-cross Abstract: Graph Retrieval-Augmented Generation (GraphRAG) faces significant challenges in complex relational retrieval tasks, particularly in densely connected knowledge graphs where the number of possible paths grows rapidly with reasoning depth. Existing GraphRAG retrieval algorithms either rely on rigid, predefined heuristics to identify relevant graph context or employ costly LLM-based reasoning to guide graph traversal. To address these limitations, we propose DotRAG, a lightweight, training-free GraphRAG retrieval algorithm that uses large

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