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--- |
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license: apache-2.0 |
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datasets: |
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- Multiverse4FM/Multiverse-1K-mixed |
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- Multiverse4FM/Multiverse-1K |
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- simplescaling/s1K-1.1 |
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base_model: |
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- Qwen/Qwen2.5-32B-Instruct |
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pipeline_tag: text-generation |
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library_name: transformers |
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--- |
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# Model Summary |
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> Multiverse-32B, built on [Multiverse](https://multiverse4fm.github.io/), is the first open-source, non-AR model to achieve scores of 54% and 46% on AIME 2024 & 2025. |
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- **Webpage:** [Multiverse](https://multiverse4fm.github.io/) |
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- **Paper:** [https://arxiv.org/abs/2506.09991](https://arxiv.org/abs/2506.09991) |
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# Use |
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The model usage is documented [here](https://github.com/Multiverse4FM/Multiverse). |
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# Evaluation |
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| Model | AIME24 | AIME25 | MATH500 | GPQA-Diamond | |
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| :--- | :---: | :---: | :---: | :---: | |
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| s1-32B | 35.4 | 25.8 | 88.6 | 48.0 | |
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| s1.1-32B | 52.9 | 41.7 | 93.4 | 62.6 | |
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| Qwen2.5-32B-Instruct | 15.8 | 10.4 | 80.4 | 47.0 | |
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| Autoregressive-32B | **54.6** | <u>45.0</u> | **92.8** | <u>61.6</u> | |
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| **Multiverse-32B-zero** | 52.1 | 44.2 | <u>92.4</u> | **63.6** | |
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| **Multiverse-32B** | 53.8 | **45.8** | 91.8 | 60.7 | |
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# Acknowledge |
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Thanks to the amazing s1 team for their s1.1 dataset as base data, and the Qwen team for their Qwen-2.5-32B-Instruct as base model. |
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# Citation Information |
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```bibtex |
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@misc{yang2025multiverselanguagemodelssecretly, |
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title={Multiverse: Your Language Models Secretly Decide How to Parallelize and Merge Generation}, |
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author={Xinyu Yang and Yuwei An and Hongyi Liu and Tianqi Chen and Beidi Chen}, |
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year={2025}, |
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eprint={2506.09991}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.LG}, |
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url={https://arxiv.org/abs/2506.09991}, |
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} |
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``` |
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