From Chunks to Functional Evidence: Function-Aware Retrieval for EDA Documentation QA

Key points

• For complex technical documentation, however, the primary bottleneck is often not model reasoning but a mismatch between a query and the way knowledge is organized for retrieval.1
• Instead of operating on isolated chunks or binary relations, we collect typed artifacts into EDA functional units.1
• We then train an encoder to align queries with functional units and combine unit retrieval with direct chunk retrieval.1
• These results support function-aware evidence organization in the evaluated EDA documentation settings.1

Sources (1)

• [1]From Chunks to Functional Evidence: Function-Aware Retrieval for EDA Documentation QA
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 03:16 AM

  Retrieval-Augmented Generation (RAG) is widely used to ground answers in documents.

  For complex technical documentation, however, the primary bottleneck is often not model reasoning but a mismatch between a query and the way knowledge is organized for retrieval.

Extractive summary: sentences quoted from the sources.