arXiv AI July 2, 2026 By Jiawen Wen, Penglei Sun, Wenjie Zhang, Suixuan Qiu, Weisheng Xu, Xiaofei Yang, Xiaowen Chu

Rule-VLN: Bridging Perception and Compliance via Semantic Reasoning and Geometric Rectification

arXiv:2604. 16993v2 Announce Type: replace Abstract: As embodied AI transitions to real-world deployment, the success of the Vision-and-Language Navigation (VLN) task tends to evolve from mere reachability to social compliance.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI

4d ago

Affordance-Conditioned Decision Making: Bridging the Semantic-Spatial Gap in Zero-Shot Cross-Floor Vision-and-Language Navigation

arXiv:2609.32292v2 Announce Type: replace-cross Abstract: Vision-and-language navigation increasingly relies on general-purpose semantic planners, yet translating correct high-level intent into relia...

By Xuekang Yang, Lu Chen, Shuang Luo, Jialing Zhu, Qi Zhang, Yue Gao, Xiang Zhang

agents robotics

arXiv Computer Vision

Sep 22

What do VLM-Based Vision-Language Navigation Models Rely on: Interpreting and Steering Policy Behavior

arXiv:2609.24576v1 Announce Type: cross Abstract: Modern Vision-Language Navigation (VLN) models rely mostly on pre-trained large Vision-Language Models (VLMs) to predict navigation actions. While th...

By D\'ebora Oliveira Makowski, Samiran Gode, Abhijeet Nayak, Marco Hutter, Cordelia Schmid, Lukas Rosenberger Schmid, Wolfram Burgard

llms agents fine-tuning multimodal safety

arXiv AI

Aug 21

Rule-Compliant Visual Spatial Planning for Multimodal Large Language Models

arXiv:2608. 20237v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) combine linguistic reasoning with visual perception, yet their ability to perform visual spatial planning under explicit or previously unseen rule constraints remains underexplored.

By Yu Chen, Ting Lei, Yaoyi Li, Jia Cai, Zhecen Wu, Yang Liu

llms multimodal benchmarks

arXiv AI

2d ago

UrbanVLA: A Vision-Language-Action Model for Urban Micromobility

arXiv:2510.23576v2 Announce Type: replace-cross Abstract: Urban micromobility applications, such as delivery robots, demand reliable navigation across large-scale urban environments while following l...

By Anqi Li, Zhiyong Wang, Jiazhao Zhang, Minghan Li, Yunpeng Qi, Zhibo Chen, Zhizheng Zhang, He Wang

robotics fine-tuning multimodal safety

arXiv AI

Jun 2

Bridging the 2D-3D Gap: A Hierarchical Semantic-Geometric Map for Vision Language Navigation

arXiv:2606. 00095v1 Announce Type: cross Abstract: Vision-Language Navigation (VLN) enables embodied agents to reach target locations in unseen environments by following language instructions.

By Kailing Li, Tianwen Qian, Lijin Yang, Yuqian Fu, Jingyu Gong, Xiaoling Wang, Liang He

llms agents robotics multimodal benchmarks

arXiv AI

Aug 11

AeroDPO: Unleashing Lightweight UAV Navigation with High-Fidelity Perception and Automated Preference Optimization

arXiv:2608. 07557v1 Announce Type: cross Abstract: Vision-Language Navigation for Unmanned Aerial Vehicles (UAV-VLN) requires rapid and reactive control in complex 3D environments.

By Peng Xu, Chengcheng Wang, Shaohua Wan

llms agents efficiency multimodal benchmarks

One email a morning, machine-written

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Affordance-Conditioned Decision Making: Bridging the Semantic-Spatial Gap in Zero-Shot Cross-Floor Vision-and-Language Navigation

What do VLM-Based Vision-Language Navigation Models Rely on: Interpreting and Steering Policy Behavior

Rule-Compliant Visual Spatial Planning for Multimodal Large Language Models

UrbanVLA: A Vision-Language-Action Model for Urban Micromobility

Bridging the 2D-3D Gap: A Hierarchical Semantic-Geometric Map for Vision Language Navigation

AeroDPO: Unleashing Lightweight UAV Navigation with High-Fidelity Perception and Automated Preference Optimization