Spaces:
Running
Running
| 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](https://arxiv.org/abs/2610.36991) | |
| - 🤗 Paper page: [hf.co/papers/2610.36991](https://huggingface.co/papers/2610.36991) | |
| - 💻 Code (MIT): [github.com/SightAndCite/SpectRAG](https://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 | |
| ```bibtex | |
| @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}, | |
| } | |
| ``` | |