Towards Data Science June 25, 2026 By angela shi

An LLM as arbiter in RAG retrieval: picking the right candidate with reasons

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Enterprise Document Intelligence [Vol. 1 #7C] - One LLM call ranks the candidates with reasons.

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Towards Data Science

Jun 24

Anchor Detection for RAG: Parallel Detectors, Then One LLM Call at the End

Enterprise Document Intelligence [Vol. 1 #7B] - Retrieval is filtering on structured tables: keywords first, TOC second, embeddings last The post Anchor Detection for RAG: Parallel Detectors, Then One LLM Call at the End appeared first on Towards Data Science .

By angela shi

llms rag

Towards Data Science

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Finding the right anchors for RAG: keyword, embedding, and TOC signals in parallel

Enterprise Document Intelligence [Vol. 1 #7B] - Retrieval is filtering on structured tables: keywords first, TOC second, embeddings last The post Finding the right anchors for RAG: keyword, embedding, and TOC signals in parallel appeared first on Towards Data Science .

By angela shi

rag

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Dispatching the Parsed RAG Question: Chunk Strategy, Model Tier, Activations, Audit

Enterprise Document Intelligence [Vol. 1 #6c] - The decisions the parser makes on top of the user string, using the document’s profile: dispatch, activations, full schema, three approaches to deciding what fires, the audit _meta block, and a broker-corpus walkthrough The post Dispatching the Parsed RAG Question: Chunk Strategy, Model Tier, Activations, Audit appeared first on Towards Data Science .

By angela shi

rag

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