microsoft/graphrag
A modular graph-based Retrieval-Augmented Generation (RAG) system
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 55%Benchmarked Graph-RAG vs. Graph-Free Multi-Hop RAG: The graph mostly bought us a massive rebuild bill, not accuracy. →
- PossiblePossibly related (embedding) · 37%RAGU: A Multi-Step GraphRAG Engine with a Compact Domain-Adapted LLM →
“Possibly related via embedding similarity 0.74 (not asserted). Timestamp check: artifact after paper (+4d).”
- PossiblePossibly related (embedding) · 32%Efficient Retrieval-Augmented Generation via Token Co-occurrence Graphs →
“Possibly related via embedding similarity 0.63 (not asserted). Timestamp check: artifact after paper (+18d).”
- PossiblePossibly related (embedding) · 30%EvoGraph-R1: Self-Evolving Multimodal Knowledge Hypergraphs for Agentic Retrieval →
“Possibly related via embedding similarity 0.58 (not asserted). Timestamp check: artifact after paper (+3d).”
- PossiblePossibly related (embedding) · 29%Query-Aware Spreading Activation for Multi-Hop Retrieval over Knowledge Graphs →
“Possibly related via embedding similarity 0.56 (not asserted). Timestamp check: artifact after paper (+18d).”
- PossiblePossibly related (embedding) · 26%GRADRAG: Cross-Component Prompt Adaptation for Coordinated Multi-Agent RAG →
“Possibly related via embedding similarity 0.56 (not asserted). Timestamp check: artifact slightly before paper (-6d).”