AI RESEARCH
Rule-Based Explanations for Retrieval-Augmented LLM Systems
arXiv CS.CL
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ArXi:2510.22689v2 Announce Type: replace If-then rules are widely used to explain machine learning models; e.g., "if employed = no, then loan application = rejected." We present the first proposal to apply rules to explain the emerging class of large language models (LLMs) with retrieval-augmented generation (RAG