activity
20242026
collaborators

10 papers

cs.CV2026

ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding

Hangjie Yuan, Yichen Qian, Zhiwei Tang +21

Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundamentally a vision-centric chall…

cs.AI2026

Agent-as-a-Router: Agentic Model Routing for Coding Tasks

Pengfei Zhou, Zhiwei Tang, Yixing Ma +8

Real-world users typically have access to multiple Large Language Models (LLMs) from different providers, and these LLMs often excel at distinct domains, yet none dominate all. Con…

cs.CV2026

Towards 3D-Aware Video Diffusion Models: Render-Free Human Motion Control with Mesh Tokenization

Jingyun Liang, Min Wei, Shikai Li +5

Diffusion models have shown remarkable success in video generation. However, whether such models are truly aware of the 3D structure underlying visual observations, rather than sim…

cs.CV2025

Few-Step Distillation for Text-to-Image Generation: A Practical Guide

Yifan Pu, Yizeng Han, Zhiwei Tang +4

Diffusion distillation has dramatically accelerated class-conditional image synthesis, but its applicability to open-ended text-to-image (T2I) generation is still unclear. We prese…

cs.CV2025

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…

cs.CV2025

Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation

Inferix Team, Tianyu Feng, Yizeng Han +13

World models serve as core simulators for fields such as agentic AI, embodied AI, and gaming, capable of generating long, physically realistic, and interactive high-quality videos.…

cs.CV2025

RAPID^3: Tri-Level Reinforced Acceleration Policies for Diffusion Transformer

Wangbo Zhao, Yizeng Han, Zhiwei Tang +7

Diffusion Transformers (DiTs) excel at visual generation yet remain hampered by slow sampling. Existing training-free accelerators - step reduction, feature caching, and sparse att…

cs.CV2025

FPSAttention: Training-Aware FP8 and Sparsity Co-Design for Fast Video Diffusion

Akide Liu, Zeyu Zhang, Zhexin Li +12

Diffusion generative models have become the standard for producing high-quality, coherent video content, yet their slow inference speeds and high computational demands hinder pract…

cs.CV2025

DyDiT++: Diffusion Transformers with Timestep and Spatial Dynamics for Efficient Visual Generation

Wangbo Zhao, Yizeng Han, Jiasheng Tang +6

Diffusion Transformer (DiT), an emerging diffusion model for visual generation, has demonstrated superior performance but suffers from substantial computational costs. Our investig…

cs.CV2024

Dynamic Diffusion Transformer

Wangbo Zhao, Yizeng Han, Jiasheng Tang +5

Diffusion Transformer (DiT), an emerging diffusion model for image generation, has demonstrated superior performance but suffers from substantial computational costs. Our investiga…