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LiteRAG: Cost-Efficient Graph-Based Retrieval-Augmented Generation

Paper recorded by Signals 4 on 2026-09-09 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-09 on arXiv · recorded by Signals 4 on 2026-09-10

Category: cs.CL · 自然语言处理 · first seen 2026-09-10

Abstract

Graph-based retrieval can improve multi-hop question answering, but existing approaches often incur high query-time costs and produce diffuse, oversized contexts that reduce generation efficiency. We present LiteRAG, a graph-based retrieval method that replaces expensive retrieval-time LLM control with query-conditioned algorithmic exploration and reasoning-chain context construction. On DistComp,

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#88 most recent of 186 cs.CL papers we have recorded · ↑ newer: Two-Token Features and Small-Large Ensembles for VLM Hallucination Det · ↓ older: The Answer Path and the Grounding Instruction in LLM Question Answerin
Cite this page: LiteRAG: Cost-Efficient Graph-Based Retrieval-Augmented Generation: the #88 most recent of 186 cs.CL papers we have recorded (as of 2026-09-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/literag-cost-efficient-graph-based-retrieval-augmented-generation.html
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