--- language: - en - ja license: cc-by-nd-4.0 pretty_name: ALE-Bench size_categories: - n<1K tags: - image - text task_categories: - image-text-to-text - reinforcement-learning - text-generation - visual-question-answering --- # ALE-Bench ## Dataset Description **ALE-Bench** is a benchmark for evaluating AI systems on score-based algorithmic programming contests. This dataset is **officially provided by [AtCoder Inc.](https://atcoder.jp/company?lang=en)**. Please be sure to check the "License" section below. Please read [our blog post](https://sakana.ai/ale-bench/) and [our paper](https://arxiv.org/abs/2506.09050) for more details. **Related resources:** - [Preprint paper (arXiv)](https://arxiv.org/abs/2506.09050) - [Sakana AI Blog (English)](https://sakana.ai/ale-bench/) - [Sakana AI Blog (Japanese)](https://sakana.ai/ale-bench-jp/) - [GitHub repository](https://github.com/SakanaAI/ALE-Bench) - [Leaderboard](https://sakanaai.github.io/ALE-Bench-Leaderboard/) ## Usage [Our Python library](https://github.com/SakanaAI/ALE-Bench) automatically downloads the data from this repository. ```python import ale_bench ale_bench_session = ale_bench.start("ahc001") ``` ## License [Creative Commons Attribution-NoDerivatives 4.0 International](https://creativecommons.org/licenses/by-nd/4.0/) ## Citation ```bibtex @article{imajuku2025ale-bench, title = {ALE-Bench: A Benchmark for Long-Horizon Objective-Driven Algorithm Engineering}, author = {Imajuku, Yuki and Horie, Kohki and Iwata, Yoichi and Aoki, Kensho and Takahashi, Naohiro and Akiba, Takuya}, journal = {arXiv preprint arXiv:2506.09050}, year = {2025} } ```