aiqbench takeMachine Learning

This article focuses on optimizing Retrieval-Augmented Generation (RAG) pipelines by introducing a specific iterative loop to refine question parsing before the retrieval phase begins. By automating steps like reading documents and re-parsing queries based on missing context, this approach directly addresses core challenges in machine learning application architecture rather than discussing general software or consumer tech.

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Loop Engineering for RAG Question Parsing: The Small Loop That Runs Before Retrieval

Towards Data ScienceJuly 19, 20261 min read

Enterprise Document Intelligence [Vol.1 #6quinquies] - Prompt engineering, then context engineering, then loop engineering. On the question side, the loop is small by design: read the doc, ask what is missing, re-parse. The post Loop Engineering for RAG Question Parsing: The Small Loop That Runs Before Retrieval appeared first on Towards Data Science.

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