| --- |
| title: README |
| emoji: 🐢 |
| colorFrom: purple |
| colorTo: purple |
| sdk: static |
| pinned: false |
| --- |
| |
| # QAFD-RAG |
|
|
| Official data and pre-built knowledge graphs for [QAFD-RAG](https://github.com/Tarzanagh/QAFD-RAG) (Query-Aware Flow Diffusion for Graph-Based RAG with Retrieval Guarantees), published at **ICLR 2026**. |
|
|
| - **Paper**: [OpenReview](https://openreview.net/pdf?id=n28wnc2QTc) |
| - **Code**: [GitHub](https://github.com/Tarzanagh/QAFD-RAG) |
| - **Website**: [qafd-rag.github.io](https://qafd-rag.github.io) |
|
|
| ## Datasets |
|
|
| | Dataset | Description | |
| |---------|-------------| |
| | [qafd/kg](https://huggingface.co/datasets/qafd/kg) | Pre-built knowledge graphs for all benchmarks (UltraDomain, Multi-hop QA, Text-to-SQL, Summarization) | |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{zhou2026qafd, |
| title={Query-Aware Flow Diffusion for Graph-Based RAG with Retrieval Guarantees}, |
| author={Zhuoping Zhou and Davoud Ataee Tarzanagh and Sima Didari and Wenjun Hu |
| and Baruch Gutow and Oxana Verkholyak and Masoud Faraki and Heng Hao |
| and Hankyu Moon and Seungjai Min}, |
| booktitle={International Conference on Learning Representations (ICLR)}, |
| year={2026} |
| } |
| |
