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@@ -51,10 +51,7 @@ solutions, the annotators' verdicts, and a commentary. They correspond to the "Q
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  The problems are drawn from publicly available mathematics competitions and previously released benchmarks, and the human-written reference solutions are collected from public Art of Problem Solving posts and official competition materials. We abide by the sources' terms and conditions and redistribute this material under [**CC BY-NC-SA 4.0**](https://creativecommons.org/licenses/by-nc-sa/4.0/) - see [`LICENSE`](LICENSE) - for non-commercial research use and with proper credit to the original competitions.
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- The terms of the original sources continue to apply to the redistributed text, independently of that license:
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-
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- - **Art of Problem Solving**: the forum content is **not available for model training** and remains subject to the applicable AoPS restrictions, which require attribution when the material is used as input to an AI system.
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- - **Official competition problems and previously released benchmarks**: typically in the public domain or released under comparable conditions, which likewise forbid use of the material for training.
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  Accordingly, this data **must not be used to train any AI model**. Users are responsible for complying with the original terms that apply to each entry.
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@@ -66,7 +63,8 @@ Work produced by us - code, results, and evaluation scripts - is published under
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  @inproceedings{petrov2026proofrank,
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  title={Not All Proofs Are Equal: Evaluating {LLM} Proof Quality Beyond Correctness},
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  author={Petrov, Ivo and Dekoninck, Jasper and Dimitrov, Dimitar I. and Vechev, Martin},
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- booktitle={Advances in Neural Information Processing Systems (NeurIPS), Evaluations and Datasets Track},
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- year={2026}
 
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  }
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  ```
 
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  The problems are drawn from publicly available mathematics competitions and previously released benchmarks, and the human-written reference solutions are collected from public Art of Problem Solving posts and official competition materials. We abide by the sources' terms and conditions and redistribute this material under [**CC BY-NC-SA 4.0**](https://creativecommons.org/licenses/by-nc-sa/4.0/) - see [`LICENSE`](LICENSE) - for non-commercial research use and with proper credit to the original competitions.
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+ The terms of the original sources continue to apply to the redistributed text, independently of that license. Namely, for official competition problems and previously released benchmarks, they typically in the public domain or released under comparable conditions, which likewise forbid use of the material for training.
 
 
 
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  Accordingly, this data **must not be used to train any AI model**. Users are responsible for complying with the original terms that apply to each entry.
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  @inproceedings{petrov2026proofrank,
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  title={Not All Proofs Are Equal: Evaluating {LLM} Proof Quality Beyond Correctness},
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  author={Petrov, Ivo and Dekoninck, Jasper and Dimitrov, Dimitar I. and Vechev, Martin},
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+ booktitle={The Fortieth Annual Conference on Neural Information Processing Systems Evaluations and Datasets Track},
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+ year={2026},
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+ url={https://openreview.net/forum?id=Zf9xKiTAom}
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  }
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  ```