重温OPD（On-Policy Distillation） Permalink
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CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning
Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) · arXiv preprint, 2026
A unified RLVR framework for dense image and video captioning, where caption quality is optimized through verifiable downstream question-answering rewards.
Recommended citation: Penghui Yang*, Long Xing*, Xiaoyi Dong, Yuhang Zang, Yuhang Cao, Yibin Wang, Yujie Zhou, Jiazi Bu, Jianze Liang, Qidong Huang, Jiaqi Wang, Feng Wu, and Dahua Lin. (2026). "CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning." arXiv preprint arXiv:2606.09393. Submitted to TPAMI.
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ResOPD: Tail Residualization for Sparse On-Policy Distillation
arXiv Preprint · arXiv preprint, 2026
An exact coarse gradient plus a sampled fine-tail residual reduces gradient variance using only the teacher’s Top-k probabilities and the sampled-token score.
Recommended citation: Penghui Yang, Long Xing, Xuanlang Dai, Ziyu Liu, Kai Chen, and Yuhang Zang. (2026). "ResOPD: Tail Residualization for Sparse On-Policy Distillation." arXiv preprint arXiv:2610.04882.
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Workshop, University 1, Department, 2015
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