Vision-Language-Action Models

Also known as VLA

These models combine vision-language backbones with action generators that produce continuous motion or discrete action tokens, often in chunks and with proprioceptive input. They are commonly trained on robot demonstrations, with flow-matching and diffusion policies, reinforcement fine-tuning, and predictive world models used to improve control and planning. Research spans tabletop and bimanual manipulation, mobile and aerial navigation, autonomous driving, and humanoid control, evaluated on benchmarks such as LIBERO, CALVIN, RoboTwin, and driving simulators. A central challenge is making broad visual and language competence translate into reliable closed-loop behavior under new objects, viewpoints, embodiments, delays, and safety constraints; benchmark success can still conceal weak instruction grounding and sim-to-real failures.

Latest papers 1,140

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

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Assistron: Bayesian Shared Autonomy with Off-the-shelf Vision-Language-Action Models
Jun 22, 2026Pinhao Song, Ze Fu, Yutong Hu +1Language-Conditioned Robot Manipulation Contact-Rich Robotic Manipulation
KU Leuven, Dept. Mechanical Engineering, Research unit Robotics, Automation and Mechatronics · KU Leuven, Dept. Electrical Engineering, Research unit Processing Speech and Images
Attacking the Trusted Imagination: Oracle-Level Integrity Attacks on Imagine-then-Act World Models
Jun 22, 2026Linghan Chen, Kaiyan Ji, Minyu GuoAdversarial Attacks Adversarial Attacks on VLA Models
Adelaide University
HiL-ResRL: A Model-Agnostic Finetuning Adapter via Human-in-the-loop Residual Reinforcement Learning
Jun 22, 2026Jingyi Liu, Zhaohong Mai, ShunSen He +5RL for Robotics Vision-Language-Action Models
1CloudRobo Lab, Huawei Cloud Computing Technologies Co., Ltd. · 2South China University of Technology.
Cloak: Zero-Shot Cross-Embodiment Manipulation by Masking the End-Effector from the VLA
Jun 22, 2026Michael Piseno, Guy Tevet, C. Karen LiuZero-Shot Robotic Manipulation Language-Conditioned Robot Manipulation
Stanford University
UniFS: Unified Fast-to-Slow Hierarchical Architecture for Vision-Language-Action Models
Jun 22, 2026Lin Sun, Zhiwei Guan, Conglin Wang +7Efficient VLM Inference Efficient VLA Model Inference
JD.com, China · Yiwu Research Institute of Fudan University, China · Tianjin University, China
PolicyTrim: Boosting Intrinsic Policy Efficiency of Vision-Language-Action Models
Jun 21, 2026Xianghui Wang, Feng Chen, Wenbo Zhang +4Efficient VLA Models Vision-Language-Action Models
1Sichuan University · 2Adelaide University · 3Beijing Institute of Technology
OpenHLM: An Empirical Recipe for Whole-Body Humanoid Loco-Manipulation
Jun 20, 2026Yingdong Hu, Haodong Zhu, Boyuan Zheng +6Humanoid Loco-Manipulation Long-Horizon Robotic Manipulation
Tsinghua University · Shanghai Qi Zhi Institute · Spirit AI
Wh0: Generative World Models as Scalable Sources of Egocentric Human Hand Manipulation Data
Jun 20, 2026Yangtao Chen, Zixuan Chen, Peiyang Wang +4HOI Generation Generalization in Robotic Manipulation
Shanghai Innovation Institute · Nanjing University · Shanghai Jiaotong University
A DVDrive Approach for doScenes Instructed Driving Challenge
Jun 19, 2026Zijian Fu, Xiangyang Chu, Mengshi Qi +3VLMs for Autonomous Driving Vision-Language-Action Models
Beijing University of Posts and Telecommunications · Xiaomi EV
UniviewVLA: A Unified Multiview Vision-Language-Action Model with World Modeling
Jun 19, 2026Tao Xu, Runhao Zhang, Zhijian Huang +7World Models for Robotics Multi-View Learning
1Tongji University · 2Shanghai Innovation Institute · 4Xiaomi EV +1
Decoupling the Declarative from the Procedural in Vision-Language-Action Models
Jun 19, 2026Nikolaos Tsagkas, Andreas Sochopoulos, Chris Xiaoxuan Lu +2Robotic Manipulation Transfer Learning
University of Edinburgh · UCL · Samsung AI Center - Cambridge
Semi-Supervised Vision-Language-Action Model
Jun 19, 2026Hongyang He, Jiuming Liu, Victor SanchezVLM Adaptation Vision-Language-Action Models
University of Warwick · University of Cambridge
ASCII Art Turns LLMs into VLA Controllers
Jun 19, 2026Yitao Jiang, Roy Xing, Luyang Zhao +3Language Model-Based Control AI Control
Dept. of Computer Science, Dartmouth College, Hanover, NH, USA. · Dept. of Electrical and Computer Engineering, Clemson University, Clemson, SC, USA. · Dept. of Mechanical and Aerospace Engineering, University of Houston, Houston, TX, USA.
VLA-FAIL: Efficient Task Failure Detection for Finetuned Vision-Language-Action Models
Jun 19, 2026Florian Seligmann, Emiliyan Gospodinov, Enes Ulas Dincer +1Mahalanobis Distance Vision-Language-Action Models
Autonomous Learning Robots Lab, Karlsruhe Institute of Technology · FZI Forschungszentrum Informatik, Karlsruhe
NAC: Neural Action Codec for Vision-Language-Action Models
Jun 19, 2026Ahad Jawaid, Yu XiangNeural Audio Codecs Residual VQ
The University of Texas at Dallas
FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation
Jun 18, 2026Duc Minh Nguyen, Nghiem Tuong Diep, Binh Gia Nguyen +20VLM Adaptation Efficient VLA Models
VinRobotics, Vietnam · Center for AI Research, VinUniversity, Vietnam · University of Utah, USA +4
SignVLA: Real-Time Sign Language-Guided Robotic Manipulation via Attention LSTM and Vision-Language-Action Models
Jun 18, 2026Ningwei Bai, Xinyu Tan, Harry Gardner +6Sign Language Translation Language-Conditioned Robot Manipulation
Department of Computer Science, University College London.
World Action Models: A Survey
Jun 18, 2026Qiuhong Shen, Shihua Zhang, Yue Liao +5Action-Conditioned Video Generation Action-Conditioned World Models
National University of Singapore
Co-VLA: Coordination-Aware Structured Action Modeling for Dual-Arm Vision-Language-Action Systems
Jun 18, 2026Yandong Wang, Jiaqian Yu, Xiongfeng Peng +8Bimanual Robotic Manipulation Vision-Language-Action Models
Donghua University, Shanghai, China · Samsung R&D Institute China-Beijing (SRCB), China · Samsung AI Center, DS Division, South Korea
Finetuning Vision-Language-Action Models Requires Fewer Layers Than You Think
Jun 18, 2026Gia-Binh Nguyen, Trong-Bao Ho, Thien-Loc Ha +18Model Compression Efficient VLA Model Inference
Center for AI Research, VinUniversity · VinRobotics · University of Arkansas +10
Pose6DAug: Physically Plausible Multi-view Object Swapping for Robot Data Augmentation
Jun 18, 2026Jonghoon Lee, Seong Hyeon Park, Byungwoo Jeon +2Multi-View Consistency Data Augmentation
1KAIST · 2Korea University · 3RLWRLD
EventVLA: Event-Driven Visual Evidence Memory for Long-Horizon Vision-Language-Action Policies
Jun 18, 2026Ganlin Yang, Zhangzheng Tu, Yuqiang Yang +10Long-Horizon Robotic Manipulation Vision-Language-Action Models
University of Science and Technology of China · Shanghai AI Laboratory · Dalian University of Technology +5
Tri-Info: Generalizable, Interpretable Failure Prediction for VLA Models via Information Theory
Jun 18, 2026Jinghan Yang, Yunchao Zhang, Wang Yuan +4Robot Failure Detection Vision-Language-Action Models
HKU Musketeers Foundation Institute of Data Science · InfoBodied AI Lab, The University of Hong Kong
Perturbation-Based Epistemic Uncertainty for Failure Detection in Vision-Language-Action Models
Jun 18, 2026Yousung Lee, Dongsoo HarUncertainty Estimation for VLA Models Robotic Manipulation
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
EquiVLA: A General Framework for Rotationally Equivariant Vision-Language-Action Models
Jun 18, 2026Thien-Loc Ha, Quang-Tan Nguyen, Trong-Bao Ho +8Robot Policy Learning Diffusion Transformer
VinRobotics · VinUniversity · DFKI +2
Mix-QVLA: Task-Evidence-Aware Mixed-Precision Quantization of Vision-Language-Action Models
Jun 17, 2026Navin Ranjan, Andreas SavakisMixed-Precision Quantization VLM Quantization
Rochester Institute of Technology Rochester, New York 14623, USA
Does VLA Even Know the Basics? Measuring Commonsense and World Knowledge Retention in Vision-Language-Action Models
Jun 17, 2026Nikita Kachaev, Andrey Moskalenko, Matvey Skripkin +10VLM Evaluation Vision-Language-Action Models
1CogAI Lab · 2FusionBrain Lab · 3IAI MSU +8
Invertible Neural Network Adapter for One-Step Flow Matching in Robot Manipulation
Jun 17, 2026Yu Zhang, Kangyi Ji, Yongxiang Zou +3Invertible Neural Networks Flow Matching
Motion-Focused Latent Action Enables Cross-Embodiment VLA Training from Human EgoVideos
Jun 17, 2026Runze Xu, Yiluo Zhang, Jian Wang +2Latent Action Learning VLM Adaptation
Department of Electronic Engineering, Tsinghua University · Tianfu Jiangxi Laboratory
Object-Centric Residual RL for Zero-Shot Sim-to-Real VLA Enhancement
Jun 17, 2026Kinam Kim, Namiko Saito, Heecheol Kim +3Reinforcement Learning Zero-Shot Robotic Manipulation
KAIST, South Korea · Microsoft Research Asia - Tokyo, Japan · The University of Tokyo, Japan

Jun 22, 2026J/K move · Enter open · S save

Assistron: Bayesian Shared Autonomy with Off-the-shelf Vision-Language-Action Models

Pinhao Song, Ze Fu, Yutong Hu, Renaud Detry

KU Leuven, Dept. Mechanical Engineering, Research unit Robotics, Automation and Mechatronics · KU Leuven, Dept. Electrical Engineering, Research unit Processing Speech and Images

Language-Conditioned Robot Manipulation Contact-Rich Robotic Manipulation Vision-Language-Action Models Shared Autonomy Assistive Robotics

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We propose Assistron, a shared autonomy model that leverages Vision-Language-Action (VLA) models to assist the user in daily activities. Our approach is grounded in two core principles: (1)~minimizing human cognitive and physical effort by leveraging VLA-driven autonomy for macro-movements, and (2)~prioritizing human intervention specifically at critical failure points. Driven by the user's verbal language commands, Assistron utilizes the VLA to autonomously execute macro-reaching trajectories, saving users' effort. In contact-rich interactions where VLAs tend to fail, Assistron employs a phase-aware interaction detection mechanism and solicits the user to intervene, in turn adjusting the VLA's action generation via flow matching guidance. Critically, our formulation eliminates the need for VLA fine-tuning, protecting its broad behavioral priors from catastrophic forgetting and ensuring the model does not become a narrow specialist. We validate our approach on a comprehensive multi-task scene recovery benchmark encompassing diverse daily manipulation skills. Empirical results demonstrate that Assistron significantly improves task success rates over pure autonomous baselines while significantly reducing human cognitive and physical workload compared to traditional teleoperation, offering a scalable, smooth, and effortless paradigm for assistive manipulation. The code is available in https://github.com/mousecpn/Assistron.git.