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cs.CV2026

MaskAlign: Token-Subset Representation Alignment for Efficient Diffusion Training

Lianyu Pang, Tianlin Pan, Cheng Da +5

Representation alignment with pretrained vision models has recently shown strong potential for accelerating diffusion transformer training. By aligning intermediate diffusion featu…

cs.CV2026

NOVA: Sparse Control, Dense Synthesis for Pair-Free Video Editing

Tianlin Pan, Jiayi Dai, Chenpu Yuan +7

Recent video editing models have achieved impressive results, but most still require large-scale paired datasets. Collecting such naturally aligned pairs at scale remains highly ch…

cs.CV2026

StableWorld: Towards Stable and Consistent Long Interactive Video Generation

Ying Yang, Zhengyao Lv, Tianlin Pan +6

In this paper, we explore the overlooked challenge of stability and temporal consistency in interactive video generation, which synthesizes dynamic and controllable video worlds th…

cs.CV2025

DiverseAR: Boosting Diversity in Bitwise Autoregressive Image Generation

Ying Yang, Zhengyao Lv, Tianlin Pan +5

In this paper, we investigate the underexplored challenge of sample diversity in autoregressive (AR) generative models with bitwise visual tokenizers. We first analyze the factors…

cs.CV2025

Dual-Expert Consistency Model for Efficient and High-Quality Video Generation

Zhengyao Lv, Chenyang Si, Tianlin Pan +4

Diffusion Models have achieved remarkable results in video synthesis but require iterative denoising steps, leading to substantial computational overhead. Consistency Models have m…

cs.CV2025

Rethinking Cross-Modal Interaction in Multimodal Diffusion Transformers

Zhengyao Lv, Tianlin Pan, Chenyang Si +4

Multimodal Diffusion Transformers (MM-DiTs) have achieved remarkable progress in text-driven visual generation. However, even state-of-the-art MM-DiT models like FLUX struggle with…