30 citations · 67 across the 14 of their papers we have counts for
14 papers
Towards Error-Free Long Video Generation
Shuning Chang, Weihua Chen, Jiasheng Tang +8
Recent advances in video generation have made minute-level synthesis possible; however, generating long videos remains challenging due to error accumulation, attribute drift, and t…
BIFE: Better Interaction, Fewer Errors for Minute-Long Video Generation
Zeyu Zhang, Jinyuan Mao, Shuning Chang +5
Long video generation is a critical step toward building realistic world models, requiring both high visual fidelity and long-range interaction consistency. Recent autoregressive d…
Lumos-1: On Autoregressive Video Generation with Discrete Diffusion from a Unified Model Perspective
Hangjie Yuan, Weihua Chen, Jun Cen +11
Autoregressive large language models (LLMs) have unified a vast range of language tasks, inspiring preliminary efforts in autoregressive (AR) video generation. Existing AR video ge…
Flow Along the K-Amplitude for Generative Modeling
Weitao Du, Shuning Chang, Jiasheng Tang +3
In this work, we propose a novel generative learning paradigm, K-Flow, an algorithm that flows along the -amplitude. Here, is a scaling parameter that organizes frequency ba…
SparseDiT: Token Sparsification for Efficient Diffusion Transformer
Shuning Chang, Pichao Wang, Jiasheng Tang +2
Diffusion Transformers (DiT) are renowned for their impressive generative performance; however, they are significantly constrained by considerable computational costs due to the qu…
Revisiting Vision Transformer from the View of Path Ensemble
Shuning Chang, Pichao Wang, Hao Luo +2
Vision Transformers (ViTs) are normally regarded as a stack of transformer layers. In this work, we propose a novel view of ViTs showing that they can be seen as ensemble networks…