Bohan22/MLS-Bench-Tasks
MLS-Bench Tasks MLS-Bench is a benchmark for machine learning science. Where most agent benchmarks reward engineering one fixed instance — clean the data, tune the pipeline, climb a leaderboard — MLS-Bench asks the harder question: can an AI agent propose a new component, loss, optimizer, or training procedure whose gain transfers across settings, seeds, datasets, and scales? The benchmark contains 140 tasks across 12 ML research domains. Each task fixes a research scaffold… See the full description on the dataset page: https://huggingface.co/datasets/Bohan22/MLS-Bench-Tasks.
| Author / organization | Bohan22 |
|---|---|
| License (as declared) | mit |
| Downloads | 3K (as reported by Hugging Face) |
| Likes | 9 |
| Created | 5 May 2026 |
| Last updated at source | 11 May 2026 |
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- 16 Oct 2026 Description: MLS-Bench Tasks MLS-Bench is a benchmark for machine learning science. Where most agent benchmarks reward engineering one fixed instance — clean the data, tune the pipeline, climb a leaderboard — MLS-Bench asks the harder question: can an A → MLS-Bench Tasks MLS-Bench is a benchmark for machine learning science. Where most agent benchmarks reward engineering one fixed instance — clean the data, tune the pipeline, climb a leaderboard — MLS-Bench asks the harder question: can an A
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