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20232026
most citedFreeU: Free Lunch in Diffusion U-Net

5 citations · 13 across the 22 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

HarnessEval-W: Agentifying the Evaluation of Visual Worlds

Weiliang Chen, Haowen Sun, Jun Gao +40

A benchmark should deliver more than a scalar score: what makes an evaluation trustworthy is the reasoning that justifies the score. This is especially critical for world models, w…

cs.AI2026

Open Evaluation Agent: Efficient and Promptable Evaluation of Visual Generative Models

Shulin Tian, Ziqi Huang, Fan Zhang +3

Recent advances in visual generative models have enabled high-quality image and video generation, but evaluating these models often demands sampling hundreds or thousands of images…

cs.CV2026

Apple-: Benchmarking Thinking with Video Towards Law-Grounded Physical Intelligence

Runmao Yao, Kairui Hu, Yukang Cao +11

Modern video generation models are increasingly hailed as emerging world models with an internalized grasp of physical law. Yet existing benchmarks largely evaluate physical plausi…

cs.CV2026

Is Your Driving World Model an All-Around Player?

Lingdong Kong, Ao Liang, Tianyi Yan +20

Today's driving world models can generate remarkably realistic dash-cam videos, yet no single model excels universally. Some generate photorealistic textures but violate basic phys…

cs.CV2026

AnimationBench: Are Video Models Good at Character-Centric Animation?

Leyi Wu, Pengjun Fang, Kai Sun +8

Video generation has advanced rapidly, with recent methods producing increasingly convincing animated results. However, existing benchmarks-largely designed for realistic videos-st…

cs.CV2026

Prompt Relay: Inference-Time Temporal Control for Multi-Event Video Generation

Gordon Chen, Ziqi Huang, Ziwei Liu

Video diffusion models have achieved remarkable progress in generating high-quality videos. However, these models struggle to represent the temporal succession of multiple events i…

cs.AI2026

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond

Meng Chu, Xuan Billy Zhang, Kevin Qinghong Lin +47

As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment dynamics becomes a central bottleneck. Agents that ma…

cs.CV2026

Demystifying Video Reasoning

Ruisi Wang, Zhongang Cai, Fanyi Pu +11

Recent advances in video generation have revealed an unexpected phenomenon: diffusion-based video models exhibit non-trivial reasoning capabilities. Prior work attributes this to a…