retrieval-augmented-generation TEC-0020Ground answers in retrieved documents
Retrieve relevant documents and generate from them, with the model deciding when retrieval is needed.
Retrieve passages for the query and generate an answer that cites them. Self-RAG extends this with reflection tokens so the model decides when to retrieve and checks whether each passage supports what it wrote.
Contexts: Retrieval-augmented QA, Chat assistant
Does it work?
supported so far2 supporting · 0 contesting sources · last moved 2026-09-04
Efficacy claims — what this technique actually moves, under which conditions, and whether that has been contested.
Needs: documents or an index to retrieve from
Fails when:
- Retrieved content carries planted instructions, or the wrong account is better represented among conflicting sources. Whatever lands in context is treated as reliable. (helps, narrowly)
1 more condition from claims reviewed by AI, listed with the claims below.
Code
- https://github.com/AkariAsai/self-rag — Self-RAG training and inference code.verified 2026-09-02
Sources
Whether a technique works is a claim. What you file here becomes a claim about this technique under the first capability it addresses, with your evidence as its source, and moves the standing above the same way a paper would.