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Skill-RAG routes searches based on knowledge gaps

The method uses hidden-state probing to detect possible knowledge gaps and direct queries to specialized retrieval strategies. It was evaluated on three question-answering datasets.

Skill-RAG explores how to route information retrieval based on possible knowledge gaps detected through hidden-state probing. The proposal aims to address misalignment between queries and evidence rather than simply repeating a search.

The study evaluated the method on HotpotQA, Natural Questions, and TriviaQA. These results describe evaluations on those datasets; by themselves, they do not establish that the method will work equally well in every application or collection.

When studying or applying the idea, first define how your team recognizes an answer that lacks adequate evidence and which sources may be consulted. Compare retrieval strategies using consistent criteria, and record limitations, errors, and results by query type.

If you use AI to analyze the paper or your own data, share only what is necessary. Remove personal data and confidential information, or apply your organization’s policy; check answers against the original sources before using them.

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