activity
20232026
most citedA Closer Look at Parameter-Efficient Tuning in Diffusion Models

3 citations · 6 across the 14 of their papers we have counts for

collaborators
Showing 2026Show all

5 papers · 1 filter

cs.CV2026

Vidu S2: Real-Time Interactive, Editable, and Spatial Video Generation

Jintao Zhang, Kai Jiang, Jintao Chen +32

We present Vidu S2, which comprises Vidu S2-Avatar, a real-time interactive digital-character model, and Vidu S2-Editing, a real-time video editing model. Moreover, we explore the…

cs.CV2026

Vidu S1: A Real-Time Interactive Video Generation Model

Jintao Zhang, Kai Jiang, Jintao Chen +24

We introduce Vidu S1, a real-time interactive video generation model supporting voice control of digital characters. Users can control video generation content at any moment throug…

cs.RO2026

Motubrain: An Advanced World Action Model for Robot Control

Motubrain Team, Chendong Xiang, Fan Bao +17

Vision-Language-Action (VLA) models generalize semantically well but often lack fine-grained modeling of world dynamics. We present Motubrain, a unified World Action Model that joi…

cs.CV2026

Geometry-Aware Rotary Position Embedding for Consistent Video World Model

Chendong Xiang, Jiajun Liu, Jintao Zhang +7

Predictive world models that simulate future observations under explicit camera control are fundamental to interactive AI. Despite rapid advances, current systems lack spatial pers…

cs.CV2026

SpargeAttention2: Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning

Jintao Zhang, Kai Jiang, Chendong Xiang +5

Many training-free sparse attention methods are effective for accelerating diffusion models. Recently, several works suggest that making sparse attention trainable can further incr…