Efficient VLA Models

VLA: Vision-Language-Action

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12 papers in the last four weeks, up 140% on the four weeks before. 0.1% of all new papers.

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VLA-ACL: Action-Consistent Visual Token Pruning for Efficient Vision-Language-Action Models
Oct 6, 2026Owen Du, Yang Yue, Jie Zhang +3Efficient VLA Models VLMs for Robotics
ETH Zurich · Tsinghua University
eRLT: Efficient VLA Reinforcement Learning via Action-Relevant Token Routing
Oct 1, 2026Dehao Huang, Jianbang Liu, Jianpan Gao +7Efficient VLA Models Robotic Manipulation
Southern University of Science and Technology, Shenzhen, China. · Beijing Zhongguancun Academy, Beijing, China. · Samsung Robotics eXperience. +2
ActionUNet: Improving Robustness of VLA Models with Efficient Multi-scale Fine-tuning
Sep 28, 2026Di Zhu, Ziheng Yan, Fang WanRobotic Control Efficient VLA Models
University of Chinese Academy of Sciences
Adjoint Guidance Flow: Amortized Critic Guidance for VLA Policies
Sep 28, 2026Jeongsol Kim, Youngjun Jun, Kyumin Choi +6Efficient VLA Models Vision-Language-Action Models
KAIST · SKKU · GIST
FailPatch: Failure Residual Patching for Vision-Language-Action Models
Sep 28, 2026Peng Yu, Jiacheng Wang, Ziheng Zhang +6Robot Policy Learning Robot Policy Adaptation
Xi’an Jiaotong University · Dexmal · Nanjing University
SLIP-VLA: Single-Step Latent Imagination for Policy Learning in Vision-Language-Action Models
Sep 27, 2026Tianfu Li, Haoxuan Xu, Wenbo Chen +7World Model Learning Visuomotor Policy Learning
The Hong Kong University of Science and Technology (Guangzhou). · The Hong Kong University of Science and Technology. · Nanyang Technological University. +1
FRAM: Trajectory-Guided Visual Feature Selection for Compact Language-Conditioned Robot Manipulation
Sep 25, 2026Hiroshi Ito, Hyogo Hiruma, Yoshiki Kanai +3Language-Conditioned Robot Manipulation Efficient VLA Models
Research & Development Group, Hitachi, Ltd., Ibaraki, 312-0034, Japan.
Recovering Aggressively Pruned Vision-Language-Action Models with Offline Hidden-State Distillation
Sep 17, 2026Chiyoung Kim, Sanghyuk Roy Choi, Minhyeok LeeEfficient VLA Models Vision-Language-Action Models
Chung-Ang University, Seoul, Republic of Korea
FIVE-VLA: Fast and EffectIVE Autonomous Driving with Recurrent Action Memory
Sep 16, 2026Kemal Oksuz, Alexandru Buburuzan, Yuhan Yao +1Memory-Augmented VLMs VLMs for Autonomous Driving
Robert Bosch GmbH, Germany · Five AI Ltd., United Kingdom
Decoupling Vision, Language, and Action for Efficient Multi-Task Robot Policies
Sep 16, 2026Xiatao Sun, Chen Liang, Ziyao Zeng +5Visuomotor Policy Learning Efficient VLA Models
Department of Computer Science, Yale University, New Haven, CT, USA. · Peking University, Beijing, China. · Digients, Singapore.
Dense to MoE Adaptation for Compact Vision Language Action Policies
Sep 15, 2026Muchun Niu, Shuang Chen, Yuzhou Wu +1Robot Policy Adaptation Efficient VLA Models
Shanghai Jiao Tong University, Shanghai, China · Tianji KernalMind Co., Ltd.
What Makes an Efficient VLA? Navigating Action-Head Design, Scaling, and Latency
Sep 12, 2026Luoyang Sun, Guoyang Xia, Fengfa Li +9Efficient VLA Models Robotic Manipulation
Institute of Automation, Chinese Academy of Sciences · University of Chinese Academy of Sciences · AI Lab, The Yangtze River Delta +4
ComVLA: Communication-Aware Split Inference for VLA Models in 6G-Connected Robotics
Sep 7, 2026Boliang Liu, Wint Yi Poe, Jingyun Di +2Efficient VLA Model Inference Efficient VLA Models
Technical University of Berlin, Berlin, Germany · Huawei Heisenberg Research Center, Munich, Germany
WISE: World-model-guided Imagination Scheduling for Efficient Post-training of Vision-Language-Action Models
Sep 3, 2026Chenhao Zhang, Hanyu Zhao, Hang Cheng +2Robot Skill Learning World Models for Robotics
1Tsinghua University · 2Beijing Academy of Artificial Intelligence (BAAI)
DriftingVLA: Native One-Step Vision-Language-Action Generation via Per-Dimension Temporal Drifting
Aug 30, 2026Yuxuan Gao, Shiqi Zhang, Yedong Shen +6Efficient VLA Model Inference Visuomotor Policy Learning
University of Science and Technology of China, Hefei 230026, China. · LYNSENSE, Shanghai, China.
LM-X: Explainable Vision--Language--Action Modeling via Progress, Event, and Uncertainty Prediction
Aug 26, 2026Jin Lou, Zhiyuan Jing, Xupeng Wang +21Robotic Control Uncertainty Estimation for VLA Models
Humanoid Robot (Shanghai) Co., Ltd. · E-surfing Digital Life Technology Co., Ltd., China Telecom
Neural Introspection Gating for Adaptive KV-Cache Reuse in Vision-Language-Action Models
Aug 11, 2026Zhijie Wu, Kento Kawaharazuka, Kei OkadaAdaptive Inference KV Caching
Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
World Tokens: Enhancing Embodied Policies with Training-Time World Modeling
Aug 10, 2026Qu Tang, Benhui Zhuang, Bo Yuan +3Efficient VLA Model Inference Efficient VLA Models
JIUTIAN Research · Zhongguancun Academy
WA-SpecDec: World-Aware Speculative Decoding for Vision-Language-Action Models
Aug 9, 2026Zikang Wen, Yuning Zhang, Dong YuanEfficient VLA Model Inference Speculative Decoding
The University of Sydney
Unified Visuomotor Targets: Supervising VLAs Beyond Physical Actions
Aug 4, 2026Zhenyang Feng, Unnat JainLatent Action Learning Visuomotor Policy Learning
Department of Computer Science, University of California, Irvine
FibVLA: An Efficient Temporal Vision-Language-Action Model with Fibonacci Sampling
Jul 31, 2026Li Lin, Wujun Xu, Weiwei Meng +3Efficient VLA Model Inference Efficient VLA Models
Southeast University, Nanjing, Jiangsu, China · Nanyang Technological University, Singapore.
TurboVLA: Real-Time Vision-Language-Action Model at 32 Hz on an RTX 4090 with <1 GB VRAM
Jul 29, 2026Hengyi Xie, Chenfei Yao, Xianjin Wu +4Efficient VLA Model Inference Efficient VLA Models
Huazhong University of Science and Technology
CoTinyVLA: Chain-of-Thought Distillation for a Sub-Billion-Parameter Vision-Language-Action Model
Jul 28, 2026Minhyeok Lee, Chiyoung Kim, Chanhoe Gu +5CoT Distillation Efficient VLA Model Inference
Chung-Ang University, Republic of Korea
MemVLN: Episodic and Procedural Memory for Vision-and-Language Navigation
Jul 26, 2026Yuqi Liu, Shengju Qian, Tianyuan Qu +5Memory-Augmented VLMs Efficient VLM Inference
1The Chinese University of Hong Kong · 2LIGHTSPEED · 3The University of Hong Kong +1
Hy-Embodied-VLM-1.0: Efficient Physical-World Agents
Jul 14, 2026Ziyi Wang, Xumin Yu, Yongming Rao +19Efficient VLA Models Multimodal Foundation Models
Tencent Robotics X Hy Vision Team Futian Laboratory
Reducing Temporal Redundancy for Efficient Vision-Language-Action Inference
Jul 14, 2026Yuzhou Wu, Yuxin Zheng, Muchun Niu +6Efficient VLA Model Inference Efficient VLA Models
1Tianji KernalMind co ltd · 2Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China · 3Shanghai Jiao Tong University, Shanghai, China +2
FabriVLA: A Lightweight Vision-Language-Action Model for Precise Multi-Task Manipulation
Jul 9, 2026Shiyuan Yang, Borong Zhang, Jizheng Zhang +5Efficient VLA Models Robotic Manipulation
University of Macau · 2Mese Technology Limited Co., Ltd. · 3FabriX team at Youibot Robotics Co., Ltd.
NativeMEM: Native Memory Compression for Long-Horizon Robotic Manipulation
Jul 7, 2026Ziye Wang, Modi Shi, Chaojun Ni +5Memory-Augmented VLMs Long-Horizon Robotic Manipulation
The University of Hong Kong · Beihang University · Peking University +2
XS-VLA: Teaching Tiny Vision-Language-Action Models with Spatial Supervision and Demonstration Conditioning
Jul 5, 2026Iok Tong Lei, Ying Jie Yap, Wei Huang +5Robot Policy Learning Language-Conditioned Robot Manipulation
Department of Computer Science and Technology, Tsinghua University, Beijing, China. · National College for Excellent Engineers, Beihang University, Beijing, China. · Independent Researcher +1
Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs
Jul 2, 2026Junhao Shi, Siyin Wang, Xiaopeng Yu +3Self-Supervised Pre-Training Efficient VLA Models
1Fudan University · 2Shanghai Innovation Institute

Oct 6, 2026, cs.ROJ/K move · Enter open · S save

VLA-ACL: Action-Consistent Visual Token Pruning for Efficient Vision-Language-Action Models

Owen Du, Yang Yue, Jie Zhang, Jiaqi Pi+2

ETH Zurich · Tsinghua University

Efficient VLA Models VLMs for Robotics Visual Token Pruning

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Vision-Language-Action (VLA) models achieve strong robotic manipulation performance but incur high computational costs from processing long token sequences at every control step, limiting real-time deployment. Visual token pruning offers a direct solution, as visual patches dominate the input sequence and contain considerable redundancy. Existing approaches, however, either rely on indirect training-free heuristics, such as attention scores and motion thresholds, or require costly fine-tuning of the base VLA model. We introduce VLA-ACL (Action Consistency Learning), which learns a lightweight visual token pruning policy through action-level supervision while keeping the base VLA model entirely frozen. The training objective encourages actions produced from pruned visual contexts to remain consistent with the full-context teacher, with ground-truth actions as auxiliary supervision. This directly ties token selection to its effect on the downstream control output. Experiments on LIBERO and real-world manipulation tasks show that VLA-ACL prunes up to 87.5% of visual tokens while retaining competitive performance, reduces computation by up to 75%, and achieves a 1.5x inference speedup. These results establish a stronger performance-efficiency trade-off than existing frozen-VLA pruning methods and demonstrate the value of action-level supervision for visual token selection. Code is available at https://github.com/du-owen/VLA-ACL.

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