Hugging Face Trending Papers

Green for Go, Red for No: Visual Grounding via Semantic Segmentation for VLA Navigation Policies

Vision-language-action (VLA) models enable robot navigation from natural language and visual goals, but remain susceptible to perceptual distractions and ambiguous scene interpretations. This paper presents the first empirical evaluation of visual grounding for VLA navigation policies.

arXiv AI

Jul 14

ABot-N1: Toward a General Visual Language Navigation Foundation Model

arXiv:2607. 10383v1 Announce Type: cross Abstract: Visual Language Navigation foundation models aim to unify deep reasoning for grounded spatial decisions with broad versatility for diverse embodied tasks.

By Ruiyan Gong, Yingnan Guo, Junjun Hu, Jintao Kong, Xiaoxu Leng, Tianlun Li, Weize Li, Fei Liu, Zhicheng Liu, Jia Lu, Minghua Luo, Chenlin Ming, Yanfen Shen, Jiyue Tao, Zhengbo Wang, Mingyang Yin, Minqi Gu, Zihao Guan, Wei Guo, Guoqing Liu, Huachong Pang, Menglin Yang, Zeqian Ye, Xiaoxiao Geng, Zhining Gu, Honglin Han, Di Jing, Hongyu Pan, Mingchao Sun, Kuan Yang, Jianfang Zhang, Yanghong Chen, Ye He, Wei Mei, Jiahao Shi, Xiangpo Yang, Yanqing Zhu, Zedong Chu, Xiaolong Wu, Mu Xu

robotics multimodal benchmarks safety

arXiv AI

Jul 24

VoLN: Vision-Only Long-Horizon Navigation---Paradigm, Benchmark, and Method

arXiv:2607. 21400v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) enables embodied agents to follow natural-language instructions.

By Jiabin Lou, Haopeng Wang, Yuanshuai Wang, Xinyu Liu, Xuxin Lv, Yuxin Guo, Lei Huang, Rongye Shi, Wenjun Wu

agents robotics benchmarks

arXiv AI

1d ago

VTInstructor: Visual Trajectory Prompting for Navigation Instruction Generation in Continuous Environments

arXiv:2608. 15284v1 Announce Type: cross Abstract: Navigation instruction generation from ego-centric RGB video in continuous environments is an important yet challenging task for human-robot interaction and scalable dataset construction.

By Haolin Yang, Yuxing Long, Zihan Yang, Hao Dong

llms agents robotics benchmarks

arXiv Machine Learning

Jul 15

APPLV: Adaptive Planner Parameter Learning from Vision-Language-Action Model

arXiv:2603. 08862v2 Announce Type: replace-cross Abstract: Autonomous navigation in highly constrained environments remains challenging for mobile robots.

By Yuanjie Lu, Beichen Wang, Zhengqi Wu, Yang Li, Xiaomin Lin, Chengzhi Mao, Xuesu Xiao

llms agents reinforcement-learning robotics fine-tuning efficiency multimodal benchmarks safety

arXiv AI

Jun 12

Foresight: Iterative Reasoning About Clues that Matter for Navigation

arXiv:2606. 12550v1 Announce Type: cross Abstract: Open-world mapless navigation from sparse language instructions requires resolving underspecified goals and inferring which environmental cues are relevant for reaching the goal.

By Arthur Zhang, Carl Qi, Donne Su, Xiangyun Meng, Amy Zhang, Joydeep Biswas

llms reinforcement-learning robotics multimodal benchmarks

arXiv AI

Jul 22

Fly0: Persistent Metric Anchoring for Zero-Shot Aerial Vision-Language Navigation

arXiv:2602. 15875v2 Announce Type: replace-cross Abstract: Current Visual-Language Navigation (VLN) methodologies face a trade-off between semantic understanding and control precision.

By Zhenxing Xu, Yihong Lu, Weidong Bao, Zhengqiu Zhu, Jingxuan Zhou, Zhichuang Wang, Ji Wang, Lihua Liu, Wei He

llms multimodal benchmarks

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 Machine Learning

Jul 1

ViTL: Temporal Logic-Guided Zero-Shot Natural Language Navigation via Vision-Language Models

arXiv:2606. 30696v1 Announce Type: cross Abstract: Enabling robots to follow natural language commands to complete zero-shot long-horizon tasks remains challenging.

By Kaier Liang, Hengde Dai, Cristian-Ioan Vasile

llms robotics multimodal

arXiv AI

Jul 8

OpenGround: Planning-based Online Perception for Open-World 3D Visual Grounding

arXiv:2512. 23020v3 Announce Type: replace-cross Abstract: 3D visual grounding aims to locate objects based on natural language descriptions in 3D scenes.

By Wenyuan Huang, Zhenyu Zhang, Zhao Wang, Zhou Wei, Ting Huang, Fang Zhao, Jian Yang

llms benchmarks

arXiv AI

Jun 9

NavOne: One-Step Global Planning for Vision-Language Navigation on Top-Down Maps

arXiv:2605. 06317v4 Announce Type: replace-cross Abstract: Existing Vision-Language Navigation (VLN) methods typically adopt an egocentric, step-by-step paradigm, which struggles with error accumulation and limits efficiency.

By Dijia Zhan, Jinyi Li, Chenxi Zheng, Shaoyu Huang, Yong Li, Jie Tang, Xuemiao Xu

multimodal benchmarks

arXiv AI

Jul 3

CoFL-S: Spatially Queryable Sector Flow Fields for Local Language-Conditioned Navigation

arXiv:2607. 02222v1 Announce Type: cross Abstract: Vision-Language Navigation has increasingly emphasized high-level instruction reasoning, memory, global map construction, and instruction decomposition, while the low-level action representation remains comparatively underexplored.

By Haokun Liu, Zhaoqi Ma, Yicheng Chen, Wentao Zhang, Masaki Kitagawa, Zicen Xiong, Jinjie Li, Moju Zhao

robotics multimodal benchmarks

arXiv AI

Jul 1

PruneGround: Plug-and-play Spatial Pruning for 3D Visual Grounding

arXiv:2606. 31148v1 Announce Type: cross Abstract: 3D Visual Grounding (3DVG) aims to localize target objects in 3D scenes given natural language descriptions.

By Duc Cao Dinh, Khai Le-Duc, Florent Draye, Chris Ngo, Terry Jingchen Zhang, Bernhard Sch\"olkopf, Zhijing Jin

llms efficiency multimodal benchmarks

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