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arXiv Computation and Language By Chaewon Kim, Seo Yeon Park

SCoNE: Selective Context-aware Neuron Editing for Robust Retrieval-Augmented Generation

Read the original on arXiv Computation and Language →

SCoNE (Selective Context-aware Neuron Editing) is a training‑free method that enhances Retrieval‑Augmented Generation (RAG) by selectively strengthening context‑aware feed‑forward network neurons identified through high attribution and high cross‑input variability. It requires only a few mining samples, no fine‑tuning, and incurs no inference‑time overhead. Experiments on multiple knowledge‑intensive question‑answering benchmarks and two LLM backbones show that SCoNE consistently outperforms competitive baseline methods.

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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