index_markov_chain_rag_tutorial

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type: index up: "Home_markov_chain_rag_tutorial"

Index — markov_chain_rag_tutorial

Catalog of all wiki pages, organized by category.

Overview

• Home — Project summary and navigation
• Markov Retrieval Tutorial — Project synthesis: what this repository is and why

Concepts

• Random Walk With Restart — The parametric Markov chain used for retrieval
• Heterogeneous Graph — Chunks, documents, and concepts as the substrate
• MiniLM Embeddings — The single embedding model used for chunks and concepts
• Path-Length Decomposition — How relevance arrives at a node, by path length
• Restart Probability — The c parameter, the geometric hop-range weighting, and calibration intuition
• Vanilla RAG Failure Mode — Why nearest-neighbor retrieval fails on tail vocabulary
• Bridge Entity — Bilingual entities that connect vocabulary clusters in the graph
• Extraction-Retrieval Co-Design — Why extraction and retrieval are one design problem

Entities

• Tutorial Figures — The three PDFs generated by run_tutorial.py
• Tutorial Corpus — The 12 manufacturing entities and 24 chunks
• Tutorial Queries — The five queries and the empirical findings

Source summaries

• README Summary — Summary of the repository's user-facing README
• Tutorial PDF Summary — Summary of docs/tutorial.pdf, the primary writeup