closed-book-qa

This paper studies internalizing documents into LoRA adapters for closed-book QA and finds that once adapter capacity is sufficient, training data quality (especially answer conciseness) is the dominant factor, outperforming architectural changes and achieving higher accuracy than BM25-RAG.