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cs.CV2026

SpatialAfford: Teaching Compact VLMs Where to Look and Where to Ground for Affordance

Yufei Zhang, Chenlu Zhan, Donghui Sun +2

Affordance grounding aims to localize the functional region for interaction, such as the handle to grasp or the button to press, rather than the whole object. This makes it more ch…

cs.CV2026

Moebius: 0.2B Lightweight Image Inpainting Framework with 10B-Level Performance

Kangsheng Duan, Ziyang Xu, Wenyu Liu +3

While 10B-level industrial foundation models have pushed the boundaries of image inpainting, their prohibitive computational costs severely hinder practical deployment. Constructin…

cs.CV2026

VideoChat-M1: Collaborative Policy Planning for Video Understanding via Multi-Agent Reinforcement Learning

Boyu Chen, Zikang Wang, Zhengrong Yue +9

By leveraging tool-augmented Multimodal Large Language Models (MLLMs), multi-agent frameworks are driving progress in video understanding. However, most of them adopt static and no…

cs.CV2026

UI-Mem: Self-Evolving Experience Memory for Online Reinforcement Learning in Mobile GUI Agents

Han Xiao, Guozhi Wang, Hao Wang +7

Online Reinforcement Learning (RL) offers a promising paradigm for enhancing GUI agents through direct environment interaction. However, its effectiveness is severely hindered by i…

cs.CV2025

LENS: Learning to Segment Anything with Unified Reinforced Reasoning

Lianghui Zhu, Bin Ouyang, Yuxuan Zhang +8

Text-prompted image segmentation enables fine-grained visual understanding and is critical for applications such as human-computer interaction and robotics. However, existing super…

cs.CV2025

GroundingSuite: Measuring Complex Multi-Granular Pixel Grounding

Rui Hu, Lianghui Zhu, Yuxuan Zhang +7

Pixel grounding, encompassing tasks such as Referring Expression Segmentation (RES), has garnered considerable attention due to its immense potential for bridging the gap between v…