Modern video generators can realize increasingly complex visual narratives, positioning the prompt enhancer (PE) as a critical bridge from concise user instructions and multimodal references to structured cinematic plans. However, existing PE evaluation relies on rendered videos, imposing substantial computational and...
Ya-Wen Shao, Yu-Bo Zhu, Zi-Yun Dai et al.· 0 citations
Simple-WAM is proposed, which simplifies future modeling into a single forward pass of fully noised video tokens and adapts the training-time noise schedule to this inference behavior, leading explicit WAMs in generalization performance with efficiency comparable to Latent WAMs.
Ren-Ping Zhou, Zan-Lin Ni, Zi-Hao Fan et al.· 0 citations
While Mamba-based models have shown strong potential for long sequence modeling, adapting them to vision is challenging due to the requirement of local neighborhood correlations and multi-directional spatial contexts for visual understanding. In this paper, we present LiAuto-MindViT, a novel hybrid vision backbone that...
Extensive experiments demonstrate that the CoDeR framework substantially extends the capabilities of existing world models, enabling long-term memory, open-ended interactions, autonomous evolution, and persistent multi-agent dynamics, while achieving state-of-the-art performance across multiple evaluation settings.
Zi-Xun Fang, Ya-Wen Shao, Kai Zhu et al.· 0 citations
This work introduces Process Aligned Policy Optimization (PAPO), a novel framework that holistically aligns the RL update with the dLLM's generative trajectory via Step-Aware Process Rewards (SPR) that transform sparse terminal rewards into dense, step-wise credit, and Entropy-Guided Historical Re-enactment that replay...
Ya-Wen Shao, Jie Xiao, Kai Zhu et al.· arXiv.org· 1 citation
OminiVR surpasses all prior methods on all six visual metrics, achieves the best audio quality, and produces natural colorization---the first method to jointly address all three aspects of audio-video generative restoration.
Xin Lu, Zihao Fan, Mingchen Zhong et al.· 1 citation
This work proposes an unsupervised low-light enhancement framework based on Group Relative Policy Optimization (GRPO), which utilizes perceptual preferences to directly optimize the diffusion policy and introduces a Sliding Window Hybrid ODE-SDE Sampling strategy that confines stochasticity to dynamic sub-intervals, th...
Yuan-Fei Bao, Dong Li, Jie Huang et al.· Proceedings of the Thirty-Fi...· 0 citations
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