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20242026
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cs.CV2026

SCOUT: Unlocking Enhanced Spatial Reasoning via Structured Chain-of-Thought and Multi-Objective Process Reward

Zile Zhou, Huining Yuan, Weichen Zhang +2

Existing Vision-Language Models (VLMs) exhibits a critical bottleneck in robust spatial reasoning. Recent reinforcement learning (RL) methods aim to close this gap with verifiable…

cs.CV2026

Uncertainty-Aware World Model for Aerial Image-Goal Navigation

Deyi Zhu, Haoyu Fan, Yinan Zhu +4

Aerial image-goal navigation requires an unmanned aerial vehicle (UAV) to reach a target location specified by a goal image. Existing world-model-based methods rank candidate traje…

cs.CV2026

Learning an Interior Layout Policy in a Domain Specific Language Action Space

Yuhao Lu, Weichen Zhang, Wenyi Xiao +2

Indoor scene layout generation is a challenging task in interior design. Existing methods often oversimplify the task by reducing room conditions to coarse 3D bounding boxes and ne…

cs.CV2026

SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation

Weichen Zhang, Kebin Liu, Fan Dang +3

Semantic segmentation in open-vocabulary scenarios presents significant challenges due to the wide range and granularity of semantic categories. Existing weakly-supervised methods…

cs.CV2026

The Point, the Vision and the Text: Does Point Cloud Boost Spatial Reasoning of Large Language Models? A Bias-Controlled Study

Weichen Zhang, Ruiying Peng, Xin Zeng +9

3D Large Language Models (LLMs) leveraging spatial information in point clouds for 3D spatial reasoning attract great attention. Despite some promising results, the advantages of p…

cs.CV2026

iWorld-Bench: A Benchmark for Interactive World Models with a Unified Action Generation Framework

Jianjie Fang, Yingshan Lei, Qin Wan +8

Achieving Artificial General Intelligence (AGI) requires agents that learn and interact adaptively, with interactive world models providing scalable environments for perception, re…