Author

Teng Hu

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Preprint Oct 2026

MORCA: Offline-to-Online Reinforcement Learning for Adaptive Cache Reuse in Video Diffusion Acceleration

Diffusion Transformers (DiTs) achieve remarkable performance in video synthesis, but their iterative denoising process suffers from high inference latency. To address this, caching has emerged as an effective acceleration strategy by capitalizing on inter-step redundancy during denoising. Existing dynamic caching metho...

Yu-Xiang Xiong, Rui-Yan Wang, Wen-Qiang Wang et al. · 0 citations

Open access Oct 2026

PAGE: Parts-Aware GuidancE for Co-Speech Gesture Portrait Video Generation

Co-speech gesture video generation aims to synthesize realistic, audio-driven portrait videos from a single reference image and a speech signal. Despite advances in visual quality, diffusion-based approaches still suffer from degraded local details and imperfect audio-visual alignment. We present PAGE (Parts-Aware Guid...

Ya-Biao Wang, Jia-Fu Wu, Yi-Cheng Xu et al. · IEEE transactions on circuit... · 0 citations

#artificial intelligence Preprint Sep 2026

DIET: Deletion-response Expert Trimming for Video Diffusion Transformers

Video diffusion transformers (DiTs) increasingly adopt mixture-of-experts (MoE) architectures to reduce active computation, but their full expert storage remains costly. Existing one-shot pruning criteria mainly rely on static activation or routing statistics and cannot capture layer-level re-routing after expert delet...

Jia-Chang Zhang, Teng Hu, Bo-Hao Feng et al. · 0 citations

Preprint Aug 2026

VicEdit: Learning to Edit Videos from Visual In-Context Examples

This work proposes Visual In-context Editing, a new paradigm elevating video editing from textual instructions to multi-modal visual guidance encompassing single image, image pair, and video pair, and curates VicEdit-400K, the first large-scale dataset for visual in-context video editing.

Yu-Ji Wang, Teng Hu, Yu-Heng Chen et al. · 0 citations

Preprint Aug 2026

Efficient Audio-Visual Generation via Synchrony-Aware Cross-Modal Sparse Attention

This work presents a synchronization-aware acceleration framework for efficient audio-visual generation by explicitly accounting for cross-modal dependence during acceleration, and improves inference efficiency while keeping video quality, audio quality, and audio-video synchronization.

Sheng-Chuan Gao, Teng Hu, Bo-Hao Feng et al. · 1 citation

Preprint Jul 2026

Cycle-World: Mitigating Error Accumulation in Long-term Video World Models via Reverse-Prediction Cycle Consistency

This work proposes Cycle-World, a novel framework designed for stable and temporally consistent long-video generation that tackles error drift by enforcing strict temporal reversibility across both the training and inference phases, and demonstrates that forward generative drift can be strictly bottlenecked by a cycle-...

Zihan Su, Teng Hu, Jiangning Zhang et al. · 1 citation