README.md

metadata

title: SpectRAG
emoji: 🐙
colorFrom: blue
colorTo: indigo
sdk: static
pinned: true
license: mit
short_description: Weighted chunk graphs for multi-hop RAG context selection
tags:
  - rag
  - retrieval-augmented-generation
  - graph
  - spectral-graph-theory
  - multi-hop-qa

SpectRAG: Weighted Chunk Graphs for Token-Budgeted Context Selection in Multi-Hop RAG

An interactive, visual walkthrough of SpectRAG. SpectRAG is a retrieval framework that replaces independent top-k ranking with context-set selection over a weighted chunk graph and its Laplacian spectrum.

• 📄 Paper: arXiv:2610.36991
• 🤗 Paper page: hf.co/papers/2610.36991
• 💻 Code (MIT): github.com/SightAndCite/SpectRAG

Highlights (MultiHopRAG & UltraDomain)

Overall gold-evidence recall	91.8% (next best 76.1%)
Exact match on inference questions	95.1%
Index size vs LightRAG	46 MB vs 274 MB (~6× smaller)
Diversity win rate (LLM judge)	> 50% vs every baseline, up to 72.5%

Citation

@misc{sahinoglu2026spectragweightedchunkgraphs,
      title={SpectRAG: Weighted Chunk Graphs for Token-Budgeted Context Selection in Multi-Hop Retrieval-Augmented Generation},
      author={Zafer Sahinoglu and Abdulazeez Mohammed and Buse Yaren Kazangirler and Cahit Berkay Kazangirler},
      year={2026},
      eprint={2610.36991},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2610.36991},
}