stanford-star/relbench-v2-extra

---

license: cc-by-sa-4.0 tags:

• relbench
• relational-deep-learning configs:
• config_name: databases data_files:
  • split: eval path: STATS/databases.parquet
• config_name: tasks data_files:
  • split: eval path: STATS/tasks.parquet---

RelBench v2 extras

Everything RelBench v2 adds to v1: the v2-only databases with their tasks, and the v2-only tasks on the v1 databases of stanford-star/relbench-v1. A v2-only task on a v1 database is a tasks/ subtree with no db/ beside it; RelBench resolves the database by name.

<dataset>/
  manifest.yaml                 # tables, primary keys, foreign-key graph, val/test timestamps
  schema.svg                    # ER diagram
  db/*.parquet                  # relational tables
  tasks/<task>/manifest.yaml    # task spec
  tasks/<task>/{train,val,test}.parquet

import relbench
relbench.load_dataset("rel-arxiv").load_task("paper-citation")   # v2-only database
relbench.load_dataset("rel-f1").load_task("results-position")    # v2-only task on a v1 database

License

CC BY-SA 4.0 for the collection. Each database keeps the license of its source; see STATS/databases.parquet.

Citation

@inproceedings{relbenchv2,
  title={RelBench v2: A Large-Scale Benchmark and Repository for Relational Data},
  author={Gu, Justin and Ranjan, Rishabh and Kanatsoulis, Charilaos and Tang, Haiming and Jurkovic, Martin and Hudovernik, Valter and Znidar, Mark and Chaturvedi, Pranshu and Shroff, Parth and Li, Fengyu and Leskovec, Jure},
  booktitle={3rd Workshop on Navigating and Addressing Data Problems for Foundation Models (DATA-FM) at ICLR 2026},
  year={2026},
  note={arXiv:2602.12606 [cs.LG]},
  url={https://arxiv.org/abs/2602.12606}
}

@inproceedings{relbench,
  title={RelBench: A Benchmark for Deep Learning on Relational Databases},
  author={Robinson, Joshua and Ranjan, Rishabh and Hu, Weihua and Huang, Kexin and Han, Jiaqi and Dobles, Alejandro and Fey, Matthias and Lenssen, Jan Eric and Yuan, Yiwen and Zhang, Zecheng and He, Xinwei and Leskovec, Jure},
  booktitle={Advances in Neural Information Processing Systems},
  year={2024}
}