| --- |
| license: apache-2.0 |
| task_categories: |
| - other |
| tags: |
| - recommendation |
| - ranking |
| - sequential-recommendation |
| --- |
| |
| # UniRank: Benchmarking Ranking Models for Unified Sequential Modeling and Feature Interaction |
|
|
| This repository contains dataset artifacts for **UniRank**, an open benchmark for unified sequential modeling and feature interaction in large-scale recommendation ranking. |
|
|
| * **Paper:** [UniRank: Benchmarking Ranking Models for Unified Sequential Modeling and Feature Interaction](https://huggingface.co/papers/2607.19987) |
| * **GitHub Repository:** [salmon1802/UniRank](https://github.com/salmon1802/UniRank) |
|
|
| ## Dataset Summary |
|
|
| UniRank standardizes chronological point-wise autoregressive supervision, multi-feedback evaluation, model implementations, data processing, and distributed training in one reproducible pipeline. |
|
|
| The benchmark evaluates unified ranking architectures on five large-scale industrial datasets from short-video, advertising, and e-commerce scenarios: |
|
|
| | Dataset | Instances | Users | Items | Fields | Tasks | Avg. length | Max. length | |
| |:--|--:|--:|--:|--:|--:|--:|--:| |
| | **QK-Video** | 493,306,303 | 4,996,176 | 3,752,235 | 10 | 4 | 99 | 6,013 | |
| | **KuaiRand** | 323,464,444 | 27,285 | 32,038,725 | 40 | 6 | 11,855 | 228,030 | |
| | **TAAC-25** | 757,207,146 | 7,706,778 | 15,707,425 | 30 | 2 | 98 | 100 | |
| | **Taobao** | 23,601,301 | 470,570 | 831,643 | 23 | 4 | 50 | 3,756 | |
| | **MerRec** | 172,304,959 | 1,697,072 | 42,577,610 | 20 | 5 | 102 | 26,576 | |
|
|
| ## Download and Usage |
|
|
| The recommended workflow is to download a ready-to-use dataset from Hugging Face to local storage. For example, to download the KuaiRand dataset: |
|
|
| ```bash |
| hf download salmon1802/KuaiRand \ |
| --repo-type dataset \ |
| --local-dir /path/to/data/KuaiRand_Video_Action |
| ``` |
|
|
| Please refer to the [GitHub Repository](https://github.com/salmon1802/UniRank) for preprocessing scripts, model configurations, and training instructions. |
|
|
| ## Citation |
|
|
| If you find this dataset or benchmark useful, please cite the paper: |
|
|
| ```bibtex |
| @article{unirank2026, |
| title={UniRank: Benchmarking Ranking Models for Unified Sequential Modeling and Feature Interaction}, |
| author={UniRank Authors}, |
| journal={arXiv preprint arXiv:2607.19987}, |
| year={2026} |
| } |
| ``` |
