RAG Evaluation Frameworks for Grounded Answer Quality
Split retrieval and generation scoring to catch hallucinations end-to-end evaluation misses.
Linh Phuong Dao
Section
7 stories in RAG Architecture.
Split retrieval and generation scoring to catch hallucinations end-to-end evaluation misses.
A four-stage pipeline ensures RAG data stays grounded instead of fabricated.
Query-time fetching forces a rethink of how web pages get split.
Dense vectors miss SKUs and keywords miss paraphrases, so fuse both.
Semantic search can't tell old from new, and that gets costly.
Fixed time limits at each pipeline stage stop timeout cascades.
Averaging citation scores hides failures, so score each rubric separately.