most citedVideo-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization

5 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Learning from Next-Frame Prediction: Autoregressive Video Modeling Encodes Effective Representations

Jinghan Li, Yang Jin, Hao Jiang +3

Recent advances in pretraining general foundation models have significantly improved performance across diverse downstream tasks. While autoregressive (AR) generative models like G…

cs.CV2024★ 2 cited

Pyramidal Flow Matching for Efficient Video Generative Modeling

Yang Jin, Zhicheng Sun, Ningyuan Li +7

Video generation requires modeling a vast spatiotemporal space, which demands significant computational resources and data usage. To reduce the complexity, the prevailing approache…

cs.CV2024

RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance

Zhicheng Sun, Zhenhao Yang, Yang Jin +7

Customizing diffusion models to generate identity-preserving images from user-provided reference images is an intriguing new problem. The prevalent approaches typically require tra…

cs.IR2024

End-to-end training of Multimodal Model and ranking Model

Xiuqi Deng, Lu Xu, Xiyao Li +10

Traditional recommender systems heavily rely on ID features, which often encounter challenges related to cold-start and generalization. Modeling pre-extracted content features can…

cs.CV2024★ 5 cited

Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization

Yang Jin, Zhicheng Sun, Kun Xu +9

In light of recent advances in multimodal Large Language Models (LLMs), there is increasing attention to scaling them from image-text data to more informative real-world videos. Co…