Vision-Language-Action Models

Also known as VLA

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249 papers in the last four weeks, up 144% on the four weeks before. 1.5% of all new papers.

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VLA-Hijack: A Transferable Patch Attack against Vision-Language-Action Models via Visual Proprioception Hijacking
May 27, 2026Jiyuan Fu, Kaixun Jiang, Jingkai Jia +7Adversarial Patch Attacks Adversarial Attacks on VLA Models
Fudan University · The Hong Kong Polytechnic University
LAST: Bridging Vision-Language and Action Manifolds via Gromov-Wasserstein Alignment
May 27, 2026Huaihai Lyu, Chaofan Chen, Yuheng Ji +4Cross-Modal Learning Vision-Language-Action Models
1MAIS, Institute of Automation, Chinese Academy of Sciences. · 2Beijing Academy of Artificial Intelligence. · 3Peking University..
General Covariant Action Modeling: Constructing Generalized Manifolds via Spatio-Temporal Decoupling
May 27, 2026Huaihai Lyu, Chaofan Chen, Mingyu Cao +2Geometric Representation Learning Vision-Language-Action Models
1MAIS, Institute of Automation, Chinese Academy of Sciences · 2Beijing Academy of Artificial Intelligence.
Colosseum V2: Benchmarking Generalization for Vision-Language-Action Models
May 26, 2026Jeremy Morgan, Hyeonho Oh, Prajwal Vijay +7Robotics Simulation Generalization in Robotic Manipulation
Department of Computer Science, University of Southern California, Los Angeles, CA, USA · Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India · Fu Foundation School of Engineering and Applied Science, Columbia University, New York, NY, USA
FineVLA: Fine-Grained Instruction Alignment for Steerable Vision-Language-Action Policies
May 26, 2026Xintong Hu, Xuhong Huang, Jinyu Zhang +11Language-Conditioned Robot Manipulation Vision-Language-Action Models
XLANG Lab, The University of Hong Kong · Qwen Team, Alibaba Inc.
Can VLA Models Learn from Real-World Data Continually without Forgetting?
May 26, 2026Jiarun Zhu, Yijun Hong, Xiaoquan Sun +5Continual Robot Learning Continual Learning for VLA Models
1HKU · 5SUSTech · 2INFIFORCE +3
A Factory-Floor Deployment Case Study of VLA Pipelines for Industrial Packaging Task: Workflow, Failures, and Lessons
May 25, 2026Brian Zhu, Philipp Schmitt, Philine Meister +12Robot Policy Learning Robotics
Siemens Corporation
Capability and Robustness Cannot Both Be Free: An Information-Theoretic Bound for Vision-Language-Action Models
May 25, 2026Jianwei TaiNeural Network Robustness Adversarial Robustness
School of Internet, Anhui University
OASIS: Observation-Action Space Alignment via SE(3) Trajectory Prediction for Robotic Manipulation
May 25, 2026Xinzhe Chen, Sihua Ren, Liqi Huang +5Visuomotor Policy Learning Robotic Manipulation
National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University
Rethinking VLM Representation for VLA Initialization
May 25, 2026Weifeng Lin, Siyuan Huang, Hao Li +5VLM Adaptation Low-Rank Adaptation
1CUHK · 4ACE Robotics · 3Peking University +1
EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models
May 25, 2026Perry Dong, Kuo-Han Hung, Tian Gao +2Robot Skill Learning Robotic RL
Stanford University
X-DiffVLA: X-Embodied Diffusion Action Heads for Vision-Language-Action Models
May 24, 2026Boyu Li, Chaoyi Xu, Haoqi Yuan +5Cross-Embodiment Robot Learning Diffusion Policy
1SKL-MAIS, Institute of Automation, Chinese Academy of Sciences · School of Artificial Intelligence, University of Chinese Academy of Sciences · 3Beijing Academy of Artificial Intelligence +2
X-Foresight: A Joint Vision-Action Causal Forecasting Network via Predictive World Modeling
May 24, 2026Baolu Li, Jingyu Qian, Rui Guo +17World Model Learning Long-Horizon Video Generation
Victor · PWM Team, XPeng Inc.
QuoVLA: Quotient Space for Vision-Language-Action Models
May 24, 2026Xuan Wang, Yinan Wu, Haoran Duan +1Representation Learning VLM Adaptation
Department of Automation Tsinghua University
Understanding the Impact of Geometric Foundation Models on Vision-Language-Action Models
May 23, 2026Yurou Yang, Muyuan Lin, Roberto Martin-Martin +43D Reconstruction Geometric Representation Learning
Amazon Personal Robotics Group · University of Texas at Austin · Massachusetts Institute of Technology
Afford-VLA: Action-Aligned Visual Planning via Internalized Affordance
May 22, 2026Runze Wang, Yuqian Fu, Yu Li +7Visual Spatial Reasoning Robotic Manipulation
1Fudan University · 2KAUST · 3SJTU +1
Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving
May 22, 2026Kewei Zhang, Jin Wang, Sensen Gao +9VLMs for Autonomous Driving End-to-End Autonomous Driving
1Peking University · 3The University of Hong Kong · 2NVIDIA +1
$π_0$ -EqM: Equilibrium Matching for Closed-Loop Vision-Language-Action Control
May 22, 2026Huanming Liu, Congsheng Xu, Jianmin Ji +1Robotic Control Vision-Language-Action Models
University of Science and Technology of China, China · Shanghai Jiao Tong University, China
GesVLA: Gesture-Aware Vision-Language-Action Model Embedded Representations
May 21, 2026Wenxuan Guo, Ziyuan Li, Meng Zhang +7Multimodal Grounding Robotic Manipulation
1Tsinghua University · 2Dexmal
From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model
May 21, 2026Bing Hu, Zaijing Li, Rui Shao +4Visuomotor Policy Learning Robotic Manipulation
Harbin Institute of Technology, Shenzhen · PengCheng Laboratory · Shenzhen Loop Area Institute +2
Agentic-VLA: Efficient Online Adaptation for Vision-Language-Action Models
May 21, 2026Ruofan Jin, Zaixi ZhangAgentic RL VLM Adaptation
Scinetics.
Pre-VLA: Preemptive Runtime Verification for Reliable Vision-Language-Action and World-Model Rollouts
May 21, 2026Zhen Sun, Yongjian Guo, Haoran Sun +6Vision-Language-Action Models VLMs for Robotics
Beihang University · JDT AI Infra · Tsinghua University +2
Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action
May 21, 2026Pengteng Li, Weiyu Guo, He Zhang +4Language-Conditioned Robot Manipulation Robotics
Thrust of Artificial Intelligence, The Hong Kong University of Science and Technology (Guangzhou), China · AI2Robotics · Department of Computer Science and Engineering, The Hong Kong University of Science and Technology Hong Kong SAR, China.
Action with Visual Primitives
May 21, 2026Weilong Guo, Yuchen Wang, Renping Zhou +5Generalization in Robotic Manipulation Visuomotor Policy Learning
Anyverse Dynamics · Tsinghua University
LVDrive: Latent Visual Representation Enhanced Vision-Language-Action Autonomous Driving Model
May 21, 2026Xiaodong Mei, Diankun Zhang, Hongwei Xie +3VLMs for Autonomous Driving World Models
The Hong Kong University of Science and Technology · Xiaomi EV
EvoScene-VLA: Evolving Scene Beliefs Inside the Action Decoder for Chunked Robot Control
May 21, 2026Chushan Zhang, Ruihan Lu, Jinguang Tong +3World Models for Robotics Vision-Language-Action Models
Australian National University · The University of Queensland · Beijing Normal University
CrossVLA: Cross-Paradigm Post-Training and Inference Optimization for Vision-Language-Action Models
May 21, 2026Zhi LiuDirect Preference Optimization Vision-Language-Action Models
Tianjin University
Lost in Fog: Sensor Perturbations Expose Reasoning Fragility in Driving VLAs
May 20, 2026Abhinaw Priyadershi, Jelena FrtunikjVLM Robustness VLMs for Autonomous Driving
NVIDIA Corporation, USA · NVIDIA GmbH, Germany
PointACT: Vision-Language-Action Models with Multi-Scale Point-Action Interaction
May 20, 2026Shizhe Chen, Paul Pacaud, Cordelia SchmidLanguage-Conditioned Robot Manipulation Point Cloud Learning
Inria, ´Ecole normale sup´erieure, CNRS, PSL Research University
DriveMA: Rethinking Language Interfaces in Driving VLAs with One-Step Meta-Actions
May 20, 2026Weicheng Zheng, Yixin Huang, Qiao Sun +2VLMs for Autonomous Driving Efficient VLA Models
Shanghai Qi Zhi Institute · Tongji University · Tsinghua University

May 27, 2026J/K move · Enter open · S save

VLA-Hijack: A Transferable Patch Attack against Vision-Language-Action Models via Visual Proprioception Hijacking

Jiyuan Fu, Kaixun Jiang, Jingkai Jia, Zhaoyu Chen+6

Fudan University · The Hong Kong Polytechnic University

Adversarial Patch Attacks Adversarial Attacks on VLA Models Vision-Language-Action Models Transfer-Based Adversarial Attacks Robustness of VLA Models Physical Adversarial Attacks

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While Vision-Language-Action (VLA) models have emerged as powerful generalist policies, their severe vulnerability to adversarial patches significantly hinders their deployment in safety-critical domains. Moreover, existing patch attacks primarily focus on white-box settings, heavily overfitting to the specific action output space of the target model, which results in poor cross-architecture transferability. To overcome this limitation, we propose VLA-Hijack, a unified adversarial framework that breaks the transferability bottleneck by exploiting a fundamental vulnerability identified in this work: before planning any motion, a VLA model must first use visual information to locate its own robotic arm within the environment. Targeting this shared visual self-localization process, our approach concurrently optimizes Attention-Guided Proprioceptive Suppression to inhibit the real robotic arm's features, and Multimodal Proprioceptive Injection to establish the patch as a surrogate "phantom embodiment". By alternating between semantic concept anchoring and visual prototype projection, VLA-Hijack effectively severs the semantic relationship between the agent's true embodiment and its control policy. Extensive experiments across diverse architectures (OpenVLA, UniVLA, and CronusVLA) demonstrate that VLA-Hijack achieves superior optimization efficiency in white-box settings and sets a new SOTA for cross-architecture and cross-domain black-box transferability.