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+ ---
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+ license: cc-by-nc-4.0
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+ library_name: transformers
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+ pipeline_tag: text-classification
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+ ---
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+
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+ # Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards
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+ This model is part of the **MAHALO** (Multi-Action-Head ALignment with PRM-guided DecOding) framework, introduced in the paper [Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards](https://huggingface.co/papers/2510.01167).
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+ MAHALO is a unified framework that standardizes PRM training across verifiable and non-verifiable settings for step-level supervision, performs vectorized multi-objective alignment with Multi-Action-Head DPO, and enables controllable inference through objective-specific weighting and PRM-guided decoding.
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+ This specific checkpoint is a sequence classification model (reward model/PRM) based on the Llama architecture.
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+ ## Resources
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+ - **Paper:** [Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards](https://huggingface.co/papers/2510.01167)
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+ - **Code:** [https://github.com/pearls-lab/multiobj-align](https://github.com/pearls-lab/multiobj-align)
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+ ## Citation
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+
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+ ```bibtex
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+ @article{shen2025simultaneous,
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+ title={Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards},
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+ author={Shen, Yiran and Xia, Yu and Chang, Jonathan and Ammanabrolu, Prithviraj},
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+ journal={arXiv preprint arXiv:2510.01167},
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+ year={2025},
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+ url={https://arxiv.org/abs/2510.01167}
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+ }
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+ ```