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LiR^3AG: A Lightweight Rerank Reasoning Strategy Framework for Retrieval-Augmented Generation

Published in The Association for the Advancement of Artificial Intelligence, 2026

We explored the reasoning strategies of reasoning models in RAG multi-hop QA tasks, finally proposed a lightweight framework that improves performance while significantly reducing reasoning overhead by integrating three modules.

Recommended citation: Chen, G., Huang, J., Xie, H., Sun, F., and Jia, T. (2025). LIR3AG: A Lightweight Rerank Reasoning Strategy Framework for Retrieval-Augmented Generation. arXiv preprint arXiv:2512.18329.
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