most citedUniVG-R1: Reasoning Guided Universal Visual Grounding with Reinforcement Learning

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cs.CV2026

Do Video Generators Track the World Across Segments? A Benchmark and Method for World-State Reasoning in Video Continuation

Yingmao Miao, Pengfei Zhang, Chaoran Xu +5

Video generators build long videos by composing shorter parts, either by generating segments one after another or by autoregressively extending chunks. Each new part usually depend…

cs.CV2026

R2M-Bench: Evaluating Revisit Memory via Relative Consistency in Interactive Video World Models

Qiwen Gu, Bingjie Gao, Rui Chen +7

High similarity between first-visit and return frames does not necessarily show that a video world model remembered the scene; the intervening rollout may simply have changed very…

cs.CV2026

DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation

DreamX Team, Rui Chen, Xiangxiang Chu +7

We present \textbf{DreamX-Phi 1.0}, an action-conditioned video world model for robotic manipulation that, given an observed frame, a language instruction, and a prescribed action…

cs.CV2026

Peak-End-Net: A Peak-End Rule Inspired Framework for Generalizable Video Aesthetic Assessment

Geng Li, Haiwen Li, Rui Chen +3

Video aesthetic assessment (VAA) aims to predict how aesthetically pleasing a video is, yet remains far less explored than other visual assessment tasks. Its progress is hindered n…

cs.CV2026

DreamX-World 1.0: A General-Purpose Interactive World Model

DreamX Team, Yancheng Bai, Rui Chen +20

DreamX-World 1.0 is a general-purpose interactive text/image-to-video world model for controllable long-horizon generation. It supports camera navigation, revisits to previously ob…

cs.CV2026

From Scale to Speed: Adaptive Test-Time Scaling for Image Editing

Xiangyan Qu, Zhenlong Yuan, Jing Tang +9

Image Chain-of-Thought (Image-CoT) is a test-time scaling paradigm that improves image generation by extending inference time. Most Image-CoT methods focus on text-to-image (T2I) g…