activity
20242026
most citedRIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers

1 citations · 2 across the 11 of their papers we have counts for

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11 papers

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.CV2026

Causal Forcing++: Scalable Few-Step Autoregressive Diffusion Distillation for Real-Time Interactive Video Generation

Min Zhao, Hongzhou Zhu, Kaiwen Zheng +6

Real-time interactive video generation requires low-latency, streaming, and controllable rollout. Existing autoregressive (AR) diffusion distillation methods have achieved strong r…

cs.CV2026

minWM: A Full-Stack Open-Source Framework for Real-Time Interactive Video World Models

Min Zhao, Hongzhou Zhu, Bokai Yan +13

Recent video diffusion foundation models have achieved remarkable progress in high-quality video generation, yet turning them into real-time interactive video world models remains…

cs.CV2026

Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation

Hongzhou Zhu, Min Zhao, Guande He +3

To achieve real-time interactive video generation, current methods distill pretrained bidirectional video diffusion models into few-step autoregressive (AR) models, facing an archi…

cs.CV2025

UltraImage: Rethinking Resolution Extrapolation in Image Diffusion Transformers

Min Zhao, Bokai Yan, Xue Yang +5

Recent image diffusion transformers achieve high-fidelity generation, but struggle to generate images beyond these scales, suffering from content repetition and quality degradation…