Role of RAG Noise in LLMs
First page

Paper summary
proposes a benchmark (NoiserBench) to measure how different kinds of noisy information affect RAG's performance; reports that from different kinds of beneficial noise studied (e.g., semantic, datatype, and illegal sentence), illegal sentence noise exhibits the most improved model performance across models and datasets.