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arXiv Computation and Language By Jinchang Zhu, Jindong Li, Yi Ding, Xiaojian Nie, Rong Fu, Shuangyong Song, Haowei He, Menglin Yang

FCPRAG: Fusion-Controller Parametric Retrieval-Augmented Generation for Stable Multi-Passage LoRA Injection

Read the original on arXiv Computation and Language →

FCPRAG introduces a fusion-controlled parametric retrieval‑augmented generation framework that uses a lightweight controller to predict per‑passage fusion scores and sample‑level calibration signals, such as a mixing gate and adaptive temperature. This approach mitigates the bottleneck of evidence‑level fusion when multiple passages are retrieved, enabling selective fusion under informative signals and conservative fusion under uncertainty. Experiments on HotpotQA, 2WikiMultiHopQA, PopQA, and ComplexWebQuestions demonstrate consistent F1 improvements over standard RAG and parametric RAG baselines, with gains up to 4.65% on 2WikiMultiHopQA and 7.55% on CWQ, while also reducing tuning cost and enhancing robustness to retrieval perturbations.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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