RAG Accuracy Depends on Question Design: Improving Accuracy Before Search with HyDE
Published:Dec 23, 2025 22:00
•1 min read
•Zenn LLM
Analysis
This article highlights a crucial aspect often overlooked in RAG (Retrieval-Augmented Generation) implementations: the quality of the initial question. While much focus is placed on optimizing chunking and reranking after the search, the article argues that the question itself significantly impacts retrieval accuracy. It introduces HyDE (Hypothetical Document Embeddings) as a method to improve search precision by generating a virtual document tailored to the query, thereby enhancing the relevance of retrieved information. The article promises to offer a new perspective on RAG search accuracy by emphasizing the importance of question design.
Key Takeaways
- •Question design is crucial for RAG accuracy.
- •HyDE improves search precision by generating virtual documents.
- •Focusing on question design offers a new perspective on RAG optimization.
Reference
“多くの場合、精度改善の議論は「検索後」の工程に集中しがちですが、実はその前段階である「質問そのもの」が精度改善を大きく左右しています。”