DOTRAG: Retrieval-Time Reasoning Along Paths
Graph Retrieval-Augmented Generation (GraphRAG) is dominated by a retrieve-then-reason paradigm, where context is retrieved using heuristics and then reasoned over. Such methods struggle to adapt to the query-specific logic required for complex multi-hop tasks, often accumulating irrelevant context or missing correct relational paths. We propose DotRAG, a training-free GraphRAG framework that reformulates retrieval as a reasoning process over paths. Our approach generates query-conditioned constraints that guide graph exploration, prune irrelevant regions, and iteratively discover relational paths without relying on explicit step-by-step reasoning chains. We introduce Division of Thought ...
| Authors | Larnell Moore, Naihao Deng, Rada Mihalcea et al. |
|---|---|
| Primary category | cs.IR |
| Published | 6 April 2026 |
| Last updated at source | 6 April 2026 |
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