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most citedRAP: Efficient Text-Video Retrieval with Sparse-and-Correlated Adapter

1 citations · 1 across the 24 of their papers we have counts for

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Showing 2026 · cs.CVShow all

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cs.CV2026

Thinking with Images without Coordinates

Meng Cao, Haoze Zhao, Yi Wang +2

Recent advances in multi-modal large language models have shifted toward the "thinking with images" paradigm to improve reasoning faithfulness, yet existing methods rely heavily on…

cs.CV2026

PAVXploreRL: Physical-Action-Visual World Model Reinforcement Learning with Action Exploration

Han Wang, Zijun Wang, Shuoshuo Xue +5

Action-conditioned world models are a key component of embodied AI, serving as scalable policy evaluators that reduce reliance on expensive real-world rollouts. To accurately captu…

cs.CV2026

AnyCrowd: Instance-Isolated Identity-Pose Binding for Arbitrary Multi-Character Animation

Zhenyu Xie, Ji Xia, Michael Kampffmeyer +9

Controllable character animation has advanced rapidly in recent years, yet multi-character animation remains underexplored. As the number of characters grows, multi-character refer…

cs.CV2026

World2Act: Latent Action Post-Training from World Model Dynamics

An Dinh Vuong, Tuan Van Vo, Abdullah Sohail +6

World Models (WMs) offer a promising mechanism for post-training Vision-Language-Action (VLA) policies by providing dynamics priors that improve generalization under task and scene…

cs.CV2026

Order from Chaos: Physical World Understanding from Glitchy Gameplay Videos

Meng Cao, Haoran Tang, Haoze Zhao +6

Understanding the physical world, including object dynamics, material properties, and causal interactions, remains a core challenge in artificial intelligence. Although recent mult…