IBM's STAIR RAG approach using table of contents for retrieval
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IBM's STAIR approach eliminates traditional RAG's chunking, embeddings, and vector databases by instead using a document's table of contents. The model learns to read a query and point directly to the relevant section (the leaf node in the table of contents hierarchy), which is then passed as context to generate answers. Tested on 18 textbooks across 6 domains, STAIR achieved 82.6% retrieval quality versus 76.9% for the DSI baseline, significantly reducing hallucinations. The main limitation is that documents must have clean, well-structured tables of contents; the researchers plan to next develop methods for generating artificial tables of contents and scaling to enterprise documents.
