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## Links
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- 📄 **arXiv Paper**: https://arxiv.org/abs/
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- 🤗 **Hugging Face Paper**: https://huggingface.co/papers/
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- 💻 **GitHub Code**: https://github.com/ModalityDance/MRM
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- 📦 **Hugging Face Collection**: https://huggingface.co/collections/ModalityDance/mrm
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If you use this model or code in your research, please cite:
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```bibtex
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@
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}
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```
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## Links
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- 📄 **arXiv Paper**: https://arxiv.org/abs/2601.18731
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- 🤗 **Hugging Face Paper**: https://huggingface.co/papers/2601.18731
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- 💻 **GitHub Code**: https://github.com/ModalityDance/MRM
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- 📦 **Hugging Face Collection**: https://huggingface.co/collections/ModalityDance/mrm
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If you use this model or code in your research, please cite:
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```bibtex
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@misc{cai2026adaptsanymetareward,
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title={One Adapts to Any: Meta Reward Modeling for Personalized LLM Alignment},
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author={Hongru Cai and Yongqi Li and Tiezheng Yu and Fengbin Zhu and Wenjie Wang and Fuli Feng and Wenjie Li},
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year={2026},
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eprint={2601.18731},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2601.18731},
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}
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```
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