New method distills enterprise knowledge into navigable agent skills for QA

Researchers have developed a new method called Corpus2Skill that enhances Retrieval-Augmented Generation (RAG) by allowing LLM agents to navigate a hierarchical skill directory derived from a document corpus. This approach enables agents to better understand the corpus structure, backtrack from unproductive search paths, and synthesize information from disparate sources. Corpus2Skill demonstrated superior performance on the WixQA enterprise customer-support benchmark compared to existing RAG methods and showed strong generalization across various RAGBench subsets, particularly for single-domain, atomic-document corpora. AI

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IMPACT Enhances RAG systems by enabling agents to navigate knowledge hierarchies, improving information retrieval and synthesis for enterprise QA.

RANK_REASON This is a research paper detailing a new method for improving RAG systems.

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• Corpus2Skill
• RAG
• LLM
• WixQA
• RAGBench
• arXiv

• paper
• product