arXiv Machine Learning

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.

arXiv Machine Learning

Jun 17

Can Vision Foundation Models Navigate? Zero-Shot Real-World Evaluation and Lessons Learned

arXiv:2603. 25937v2 Announce Type: replace-cross Abstract: Visual Navigation Models (VNMs) promise generalizable, robot navigation by learning from large-scale visual demonstrations.

By Maeva Guerrier, Karthik Soma, Jana Pavlasek, Giovanni Beltrame

llms diffusion robotics benchmarks

arXiv AI

Jul 24

Vision-Language-Policy Model for Dynamic Robot Task Planning

arXiv:2512. 19178v2 Announce Type: replace-cross Abstract: Bridging the gap between natural language commands and autonomous execution in unstructured environments remains an open challenge for robotics.

By Jin Wang, Kim Tien Ly, Jacques Cloete, Jin Jin, Nikos Tsagarakis, Ioannis Havoutis

llms agents robotics fine-tuning multimodal

arXiv AI

Jun 10

RoboGPT-R1: Enhancing Robot Task Planning with Reinforcement Learning

arXiv:2510. 14828v3 Announce Type: replace Abstract: Improving the reasoning capabilities of embodied agents is crucial for robots to complete complex human instructions in long-view manipulation tasks successfully.

By Jinrui Liu, Bingyan Nie, Boyu Li, Yaran Chen, Yuze Wang, Shunsen He, Haoran Li

llms agents reinforcement-learning robotics fine-tuning benchmarks

arXiv AI

Jun 16

LaWAM: Latent World Action Models for Efficient Dynamics-Aware Robot Policies

arXiv:2606. 15768v1 Announce Type: cross Abstract: Vision-Language-Action models (VLAs) leverage large-scale vision-language pretraining for semantic robot control, but often lack explicit foresight into how robot actions change the scene.

By Jialei Chen, Kai Wang, Kang Chen, Shuaihang Chen, Feng Gao, Wenhao Tang, Zhiyuan Li, Weilin Liu, Zhuyu Yao, Boxun Li, Yuanbo Xu, Chao Yu

diffusion robotics multimodal benchmarks

arXiv AI

Jun 30

LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving

arXiv:2606. 29879v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) provide powerful semantic understanding and commonsense reasoning for End-to-End Autonomous Driving (E2E-AD) planning.

By Chen Yang, Yuhao Wei, Ze Xu, Ziheng Zou, Shuang Liang, Delin Ouyang, Lingfeng Qi, Jie Li, Guofa Li

llms agents robotics multimodal benchmarks

arXiv AI

Aug 6

Explicit Language Memory for Long-Horizon Planning in Vision-Language-Action Models

arXiv:2608. 04765v1 Announce Type: cross Abstract: Vision-language-action (VLA) models provide a unified paradigm for connecting visual perception, language understanding, and robotic control.

By Houze Xu, Jizhong Li, Ziyi Ye

llms nlp robotics fine-tuning multimodal

arXiv Machine Learning

Jun 10

Task Robustness via Re-Labelling Vision-Action Robot Data

arXiv:2606. 10918v1 Announce Type: cross Abstract: The recent trend in scaling models for robot learning has resulted in impressive policies that can perform various manipulation tasks and generalize to novel scenarios.

By Artur Kuramshin, \"Ozg\"ur Aslan, Cyrus Neary, Glen Berseth

llms robotics multimodal

arXiv AI

Jul 24

Robostral Navigate

arXiv:2607. 20785v1 Announce Type: cross Abstract: Deploying navigation systems at scale requires a recipe that minimizes sensor assumptions, generalizes across robot embodiments, and trains efficiently.

By Arjun Majumdar, Avinash Sooriyarachchi, Benjamin Tibi, Chris Bamford, Elliot Chane-Sane, Guillaume Lample, Khyathi Raghavi Chandu, Ludovic Ho Fuh, Mathieu Poiree, Olivier Duchenne, Rosalie Millner, Srijan Mishra, Theo Cachet, Thomas Chabal

llms reinforcement-learning 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 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

Jun 30

RoboGaze: Evaluating Robot World Models via Structured Vision-Language Analysis

arXiv:2606. 28385v1 Announce Type: cross Abstract: Recent advances in robot world models enable synthetic video generation for embodied prediction and planning.

By Minh-Loi Nguyen, Nghiem Tuong Diep, Hung Khang Nguyen, Minh Le, Doanh Le Thien, Hoang H. Tran, Dung D. Le, Vu N. Duong, Daniel Sonntag, An Thai Le, Duy Minh Ho Nguyen, Vien Anh Ngo, Tran Van Nhiem

llms agents diffusion robotics multimodal benchmarks safety

arXiv AI

Jun 18

EffiNav: Fusing Depth and Vision-Language for Efficient Object Goal Navigation

arXiv:2606. 18634v1 Announce Type: cross Abstract: To locate a target object while exploring the unknown environment is a fundamental capability for autonomous agents, with applications ranging from search-and-rescue to field robots.

By Zecheng Yin, Benedict Jun Ma

agents robotics multimodal benchmarks

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