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README.md
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sdk: static
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license: apache-2.0
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short_description: Rubric-Informed Selective Exploration
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---
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#
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author = {Park, Keunhong and Sinha, Utkarsh and Barron, Jonathan T. and Bouaziz, Sofien and Goldman, Dan B and Seitz, Steven M. and Martin-Brualla, Ricardo},
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title = {Nerfies: Deformable Neural Radiance Fields},
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journal = {ICCV},
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year = {2021},
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}
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```
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sdk: static
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pinned: false
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license: apache-2.0
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short_description: Rubric-Informed Selective Exploration
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---
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# RISE-RL: Rubric-Informed Selective Exploration for Open-Ended Reinforcement Learning
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Official project page for **RISE-RL**.
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- **Paper:** https://arxiv.org/abs/2608.09123
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- **PDF:** https://arxiv.org/pdf/2608.09123
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- **Project Page:** https://huggingface.co/spaces/houkunkun/RISE-RL
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## Authors
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Jinkun Hou, Zhuo Liu, Huimin Ren, Hongsheng Xin, Pan Zhou, Kun Zhan
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## Abstract
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RISE-RL is a rubric-informed selective exploration method for open-ended reinforcement learning. It uses repeatedly missed rubric
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criteria to elicit privileged trajectories that are difficult to discover through unguided exploration alone.
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For the complete abstract and experimental results, see our paper:
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https://arxiv.org/abs/2608.09123
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## Citation
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```bibtex
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@article{hou2026riserl,
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title = {RISE-RL: Rubric-Informed Selective Exploration for Open-Ended Reinforcement Learning},
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author = {Hou, Jinkun and Liu, Zhuo and Ren, Huimin and Xin, Hongsheng and Zhou, Pan and Zhan, Kun},
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journal = {arXiv preprint arXiv:2608.09123},
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year = {2026}
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}
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