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cs.CV2026

SpatioLM: Towards General Physical Spatial Intelligence in Vision-Language Models

Jing Wu, Jianhua Wu, Jiayi Guan +5

Vision-Language Models (VLMs) perform well on commonsense reasoning tasks but struggle with visual spatial reasoning. Most existing solutions introduce extra 3D prior inputs or ext…

cs.CV2026

MeanFuser: Fast One-Step Multi-Modal Trajectory Generation and Adaptive Reconstruction via MeanFlow for End-to-End Autonomous Driving

Junli Wang, Yinan Zheng, Xueyi Liu +9

Generative models have shown great potential in trajectory planning. Recent studies demonstrate that anchor-guided generative models are effective in modeling the uncertainty of dr…

cs.CV2026

SEF-MAP: Subspace-Decomposed Expert Fusion for Robust Multimodal HD Map Prediction

Haoxiang Fu, Lingfeng Zhang, Hao Li +7

High-definition (HD) maps are essential for autonomous driving, yet multi-modal fusion often suffers from inconsistency between camera and LiDAR modalities, leading to performance…

cs.CV2026

DriveWorld-VLA: Unified Latent-Space World Modeling with Vision-Language-Action for Autonomous Driving

Feiyang jia, Lin Liu, Ziying Song +4

End-to-end (E2E) autonomous driving has recently attracted increasing interest in unifying Vision-Language-Action (VLA) with World Models to enhance decision-making and forward-loo…

cs.CV2025

Is your VLM Sky-Ready? A Comprehensive Spatial Intelligence Benchmark for UAV Navigation

Lingfeng Zhang, Yuchen Zhang, Hongsheng Li +7

Vision-Language Models (VLMs), leveraging their powerful visual perception and reasoning capabilities, have been widely applied in Unmanned Aerial Vehicle (UAV) tasks. However, the…