activity
20242026
most citedVideo-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization

5 citations · 7 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2026

TrajCFG: Token-Wise Classifier-Free Guidance via Denoising Trajectory Feedback

Jingyu Liu, Hao Jiang, Yikang Ding +6

Classifier-free guidance (CFG) typically applies a shared scale to all latent tokens, although their velocity predictions evolve differently during sampling. We introduce Trajector…

cs.CV2026

LoomVideo: Unifying Multimodal Inputs into Video Generation and Editing

Jianzong Wu, Hao Lian, Jiongfan Yang +12

Developing unified video generation and editing models capable of interpreting interleaved multimodal inputs is a promising yet challenging frontier field. Existing unified framewo…

cs.IR2026

OneReason Technical Report

OneRec Team, Biao Yang, Boyang Ding +81

Generative recommendation models in the OneRec family have been widely deployed in many real-world services, such as short-video, live-streaming, advertising, and e-commerce. Howev…

cs.LG2026

Balancing Image Compression and Generation with Bootstrapped Tokenization

Haozhe Chi, Jinghan Li, Hao Jiang +4

Despite progress in image tokenization, standard methods encode redundant information by mixing all granularities within each token, thus redundancy persists between tokens. The mi…

cs.CV2026

Food-R1: A Unified Multi-Task Food Vision-Language Model with Reinforcement Learning

Yu Zhu, Yongkang Li, Wenjie Zhu +5

Recent studies have explored Vision-Language Models (VLMs) for food analysis. However, most existing methods rely primarily on supervised fine-tuning (SFT), which often limits reas…

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.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…