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HyperAlign-Bench
This repository contains the released HyperAlign-Bench data bundle for the paper Hypergraph as Language.
HyperAlign-Bench is a benchmark for evaluating high-order association modeling in hypergraph-language alignment. It provides vertex classification and hyperedge classification tasks under the same question-answering protocol used by Hyper-Align.
The released bundle includes processed hypergraph tensors, task samples, prebaked samples, Qwen3-Embedding-0.6B features, and overview features for five datasets.
Files
arxiv_hg/
cora_cc/
pubmed/
dblp/
imdb/
Each dataset directory follows this structure:
processed_data.pt
meta.json
samples/
embeddings/qwen3emb_0.6b/
overview/qwen3emb_0.6b/
processed_data.ptcontains the processed hypergraph data.meta.jsoncontains dataset metadata.samples/contains the VC and HEC task samples.embeddings/qwen3emb_0.6b/contains node and hyperedge text features.overview/qwen3emb_0.6b/contains overview features used by the released Hyper-Align pipeline.
For code, setup, and evaluation instructions, see the GitHub repository:
https://github.com/Mengqi-Lei/Hypergraph-as-Language
License
The HyperAlign-Bench release is distributed under the Apache License 2.0.
Qwen3-Embedding-0.6B is not redistributed here as a model. Users must comply with the license and terms of the upstream model repository:
Qwen/Qwen3-Embedding-0.6B
Citation
If you use this dataset, please cite:
@article{lei2026hypergraph,
title={Hypergraph as Language},
author={Lei, Mengqi and Xie, Guohuan and Ying, Shihui and Du, Shaoyi and Yong, Jun-Hai and Li, Siqi and Gao, Yue},
journal={arXiv preprint arXiv:2605.21858},
year={2026}
}
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