Vision-Language-Action (VLA) models typically map visual observations and linguistic instructions directly to control signals. This "black-box" mapping forces a single forward pass to simultaneously handle instruction interpretation, spatial grounding, and low-level control, often leading to poor spatial precision and limited robustness in out-of-distribution scenarios. To address these limitations, we propose VP-VLA, a dual-system framework that decouples high-level reasoning and low-level execution via a structured visual prompting interface. Specifically, a "System 2 Planner" decomposes complex instructions into sub-tasks and identifies relevant target objects and goal locations. These spatial anchors are rendered directly within the native RGB observation space as modality-consistent visual prompts, such as crosshairs and bounding boxes. This avoids the modality mismatch introduced by dense masks, affordance maps, or additional control-specific representations. Guided by these prompts and enhanced by a novel auxiliary visual grounding objective during training, a "System 1 Controller" reliably generates precise low-level execution motions. Extensive experiments in simulation and real world demonstrate that VP-VLA surpasses state-of-the-art end-to-end baselines including QwenOFT and GR00T-N1.6. Project page: https://visualprompt-vla.github.io/
MAP-VLA: Memory-Augmented Prompting for Vision-Language-Action Model in Robotic Manipulation
Nanyang Technological University（南洋理工大学）；VinUniversity（文大学）；Beijing University of Posts and Telecommunications（北京邮电大学）；Tsinghua University（清华大学）；South China University of Technology（华南理工大学）
IA-VLA: Input Augmentation for Vision-Language-Action models in settings with semantically complex tasks
Intelligent Robotics Group at the Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University（Aalto大学电气工程学院电气工程与自动化系智能机器人组）；Biomimetics and Intelligent Systems Group at the Faculty of Information Technology and Electrical Engineering, University of Oulu（奥卢大学信息科技与电气工程学院仿生学与智能系统组）；Section of Mechanical Technology at the Department of Engineering Technology and Didactics, Technical University of Denmark（丹麦技术大学工程技术与教学系机械技术部门）
MMaDA-VLA: Large Diffusion Vision-Language-Action Model with Unified Multi-Modal Instruction and Generation
Westlake University（西湖大学）；Zhejiang University（浙江大学）；East China University of Science and Technology（华东理工大学）；Huawei Celia Team（华为Celia团队）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；OpenHelix Robotics
DySL-VLA: Efficient Vision-Language-Action Model Inference via Dynamic-Static Layer-Skipping for Robot Manipulation
Institute for Artificial Intelligence（人工智能研究院）；School of Integrated Circuits, Peking University（集成电路学院，北京大学）；Shenzhen Institute of Artificial Intelligence（深圳人工智能研究所）；School of Electronics Engineering and Computer Science, Peking University（电子工程与计算机科学学院，北京大学）；Beijing Advanced Innovation Center for Integrated Circuits（北京集成电路先进制造创新中心）
Latent Reasoning VLA: Latent Thinking and Prediction for Vision-Language-Action Models
Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University（西安交通大学人工智能与机器人研究院）；Beijing Academy of Artificial Intelligence（北京人工智能研究院）；Institute of Automation, University of Chinese Academy of Sciences（中国科学院自动化研究所）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）
TaF-VLA: Tactile-Force Alignment in Vision-Language-Action Models for Force-aware Manipulation
Beihang University（北航大学）；ShanghaiTech University（上海科技大学）；Beijing Institute for General Artificial Intelligence（北京一般人工智能研究院）；The University of Hong Kong（香港大学）
DAM-VLA: A Dynamic Action Model-Based Vision-Language-Action Framework for Robot Manipulation
Advanced Research Lab, Samsung R&D Institute China-Beijing (SRCB)（三星研发中心中国北京先进研究实验室）；Samsung AI Center, DS Division（三星人工智能中心，DS部门）；Hanyang University ERICA（翰洋大学ERICA）
Long-VLA: Unleashing Long-Horizon Capability of Vision Language Action Model for Robot Manipulation
Westlake University（西湖大学）；Zhejiang University（浙江大学）；Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing（北京未来区块链与隐私计算高精尖创新中心）；University of Electronic Science and Technology of China（电子科技大学）
VLAMotor: Test-Guided Enhancement of Vision-Language-Action Models via Agent-BasedData Synthesis
School of computing and data science, Nanyang Technological University（计算与数据科学学院，南洋理工大学）；School of Software Engineering, Sun Yat-sen University（软件工程学院，中山大学）；GuangDong Engineering Technology Research Center of Blockchain, China（区块链工程技术研发中心，中国）；Northwest A&F University（西北农林科技大学）
Recurrent-Depth VLA: Implicit Test-Time Compute Scaling of Vision-Language-Action Models via Latent Iterative Reasoning
Stanford University（斯坦福大学）；Technical University of Munich（慕尼黑技术大学）；University of Washington（华盛顿大学）；Allen Institute for Artificial Intelligence（人工智能研究院）
VLAConf: Calibrated Task-Success Confidence for Vision-Language-Action Models
Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China（南方科技大学电子与电气工程系，深圳，中国）；Zhongguancun Academy, Beijing, China（中关村学院，北京，中国）；National Cybersecurity Academy, Wuhan University, Wuhan, China（武汉大学国家网络安全学院，武汉，中国）
VLA-Adapter: An Effective Paradigm for Tiny-Scale Vision-Language-Action Model
Beijing University of Posts and Telecommunications（北京邮电大学）；Westlake University（西湖大学）；Zhejiang University（浙江大学）；OpenHelix Team（OpenHelix团队）；State Key Laboratory of Networking and Switching Technology（网络与交换技术国家重点实验室）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
AIR-VLA: Vision-Language-Action Systems for Aerial Manipulation
The Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Automation, Beijing Institute of Technology（北京理工大学自动化学院）；School of Information and Intelligent Engineering, University of Sanya（三亚大学信息与智能工程学院）；School of Mechanical and Vehicle Engineering, Hunan University（湖南大学机械与车辆工程学院）；State Key Lab of Intelligent Transportation Systems, School of Transportation Science and Engineering, Beihang University（北京航空航天大学交通科学与工程学院）
ReMem-VLA: Empowering Vision-Language-Action Model with Memory via Dual-Level Recurrent Queries
Technical University of Munich（慕尼黑技术大学）；Huawei Heisenberg Research Center（华为海森堡研究中心）；University of Freiburg（弗赖堡大学）；Nanjing University（南京大学）；Huawei Technologies（华为技术）
RoboNurse-VLA: Robotic Scrub Nurse System based on Vision-Language-Action Model
Multi-Scale Medical Robotics Centre, Ltd., The Chinese University of Hong Kong（香港中文大学多尺度医疗机器人中心有限公司）；Istituto Italiano di Tecnologia（意大利技术研究院）；Department of Surgery, The Chinese University of Hong Kong（香港中文大学外科系）
Token Expand-Merge: Training-Free Token Compression for Vision-Language-Action Models
College of Science and Engineering, Hamad Bin Khalifa University（1 科学与工程学院，哈马德·本·卡西姆大学）；Mohamed bin Zayed University of Artificial Intelligence（2 摩萨·本·扎耶德人工智能大学）；College of Computer Science and Technology, Zhejiang University（3 计算机科学与技术学院，浙江大学）
TA-VLA: Elucidating the Design Space of Torque-aware Vision-Language-Action Models
Beijing Academy of Artificial Intelligence, BAAI（北京人工智能研究院）；Institute for AI Industry Research (AIR), Tsinghua Univeristy（清华大学人工智能产业研究院）；Nanyang Technological University（南洋理工大学）
SLIP-VLA: Single-Step Latent Imagination for Policy Learning in Vision-Language-Action Models
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；The Hong Kong University of Science and Technology（香港科技大学）；Nanyang Technological University（南洋理工大学）；Zhejiang University（浙江大学）
FPC-VLA: A Vision-Language-Action Framework with a Supervisor for Failure Prediction and Correction
The Institute of Robotics and Automatic Information System（机器人与自动信息系统研究所）；Tianjin Key Laboratory of Intelligent Robotics（智能机器人天津重点实验室）；TBI Center, Nankai University, Tianjin 300350, China（南开大学天津中心）；Faculty of Robot Science and Engineering, Northeastern University, Shenyang 110819, China（机器人科学与工程学院）；The State Key Laboratory of Internet of Things for Smart City（智能城市物联网国家重点实验室）；Centre for Artificial Intelligence（人工智能中心）；Department of Electromechanical Engineering, University of Macau, Macau SAR, China（机电工程系，澳门大学）
VLA-Reasoner: Empowering Vision-Language-Action Models with Reasoning via Online Monte Carlo Tree Search
School of Electrical and Electronic Engineering, Nanyang Technological University（南洋理工大学电子与电气工程学院）；Tsinghua Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications（北京邮电大学智能工程与自动化学院）
CAC-VLA: Context-Gated Action Conditioning for Vision-Language-Action Models
University of Science and Technology of China (USTC)（中国科学技术大学）；Institute of Artificial Intelligence, Hefei Comprehensive National Science Center（合肥综合性国家科学中心人工智能研究院）
S-squared-VLA: Decoupling Semantic and Spatial Streams in Vision-Language-Action Models for Autonomous Driving
School of Mechanical and Electronic Engineering, Wuhan University of Technology（武汉理工大学机电工程学院）；Intelligent Transportation Systems Research Center, Wuhan University of Technology（武汉理工大学智能交通系统研究中心）；School of Computer Science and Artificial Intelligence, Wuhan University of Technology（武汉理工大学计算机科学与人工智能学院）
RLinf-VLA: A Unified and Efficient Framework for Reinforcement Learning of Vision-Language-Action Models
Tsinghua University（清华大学）；Zhongguancun Academy（中关村学院）；Infinigence AI；Peking University（北京大学）；UC Berkeley（加州大学伯克利分校）；Harbin Institute of Technology（哈尔滨工程学院）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）
VLA^2: Empowering Vision-Language-Action Models with an Agentic Framework for Unseen Concept Manipulation
Zhejiang University（浙江大学）；MiLAB, Westlake University（西湖大学 MiLAB）；Southern University of Science and Technology（南方科技大学）；Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
