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20242026
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cs.CV2026

VideoArgus: Agentic Rubric-Grounded Unified Evaluation for Video Generation and Editing

Ziyun Zeng, Zixuan Wang, Yongsheng Yu +2

Evaluating generated videos remains challenging because existing benchmarks rely on fixed evaluation content, cover only a subset of generation and editing settings, and provide li…

cs.CV2026

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments

Haoyu Chen, Kaichen Zhou, Hang Hua +11

Video generation models aspire to simulate dynamic environments, and several benchmarks now evaluate memory consistency across frames. However, most assess consistency only while t…

cs.CV2026

Agent Skills Should Go Beyond Text: The Case for Visual Skills

Binxiao Xu, Ruichuan An, Bocheng Zou +1

Reusable skills are a key mechanism for extending agent capabilities, allowing agents to accumulate experience and solve increasingly complex tasks. Yet most existing skill-learnin…

cs.CV2026

Aurora: Unified Video Editing with a Tool-Using Agent

Yongsheng Yu, Ziyun Zeng, Zhiyuan Xiao +4

Recent video editing models have converged on a unified conditioning design: a single diffusion transformer jointly consumes text, source video, and reference images, and one set o…

cs.CV2026

MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents

Ziyun Zeng, Hang Hua, Bocheng Zou +3

Recent GUI agents have made substantial progress in visual grounding and action prediction, yet they remain brittle in long-horizon tasks that require maintaining task state across…

cs.CV2026

Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty?

Yichen Feng, Yuetai Li, Chunjiang Liu +14

Multimodal large language models (MLLMs) are now routinely deployed for visual understanding, generation, and curation. A substantial fraction of these applications require an expl…