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20242026
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cs.CV2026

VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning

Junxiang Xu, Ruisi Wang, Fanyi Pu +49

Native visual reasoning treats visual generation as the medium of reasoning itself: visual states (i.e. images and videos) are not merely inputs to be understood or outputs to be r…

cs.CV2026

PhyGround: Benchmarking Physical Reasoning in Generative World Models

Juyi Lin, Arash Akbari, Yumei He +13

Generative world models are increasingly used for video generation, where learned simulators are expected to capture the physical rules that govern real-world dynamics. However, ev…

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…

cs.CV2026

A Very Big Video Reasoning Suite

Maijunxian Wang, Ruisi Wang, Juyi Lin +53

Rapid progress in video models has largely focused on visual quality, leaving their reasoning capabilities underexplored. Video reasoning grounds intelligence in spatiotemporally c…

cs.CV20261 cited

Egocentric Bias in Vision-Language Models

Maijunxian Wang, Yijiang Li, Bingyang Wang +6

Visual perspective taking--inferring how the world appears from another's viewpoint--is foundational to social cognition. We introduce FlipSet, a diagnostic benchmark for Level-2 v…

cs.CV2025

Video Models Start to Solve Chess, Maze, Sudoku, Mental Rotation, and Raven' Matrices

Hokin Deng

We show that video generation models could reason now. Testing on tasks such as chess, maze, Sudoku, mental rotation, and Raven's Matrices, leading models such as Sora-2 achieve si…