Tactile-Vision-Language-Action Models

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21 papers3 papers in the last four weeks, down 40% on the four weeks before. 0.0% of all new papers.

T-WLA: Bridging Slow Vision and Fast Touch
Oct 20, 2026Kaichen Zhou, Yuzhen Chen, Hannah Yao +14Tactile-Vision-Language-Action Models Contact-Rich Robotic Manipulation
Massachusetts Institute of Technology · Harvard University · University of California, Davis +1
GPT-6-Astra Understands Touch and Outperform Vision--Tactile--Language--Action Models
Oct 20, 2026Ziyong Wang, Yupei Lin, Runxuan Huang +3Tactile-Vision-Language-Action Models Robot Policy Learning
Sun Yat-sen University · X-Era AI Lab · The Hong Kong Polytechnic University
Physical Words: A Vocabulary for Structuring Latent Reasoning in Robot Manipulation
Oct 19, 2026Jiaming Liu, Xinghao Zhu, Yiming Zhang +8Robot Foundation Models Robotic Manipulation
NVIDIA · Peking University · UC Berkeley
SimpleTouch: Can Vision-Language-Action Models Master Contact-Rich Manipulation Without Tactile Policy Pretraining?
Oct 2, 2026Chen Yang, Linzhe Shi, Changjie Wu +7Tactile-Vision-Language-Action Models Contact-Rich Robotic Manipulation
Tsinghua University · Amap, Alibaba Group · Hong Kong Polytechnic University
VT-Bridge: Bridging Pretrained Foundation VLAs to VTLAs via Lightweight Residual Adaptation
Sep 18, 2026Yansong Wu, Tuo Yang, Rongping Zhao +5Tactile-Vision-Language-Action Models Contact-Rich Robotic Manipulation
Technical University of Munich, Germany · Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE · Shanghai University, China
ForeTac-VLA: A Forecasting-Based Tactile-Vision-Language-Action Model for Contact-Rich Robotic Manipulation
Sep 17, 2026Zhengyu Tao, Xin Li, Xin WangTactile-Vision-Language-Action Models Contact-Rich Robotic Manipulation
Texas A&M University, College Station, TX 77843, USA
STAR: Sparse Tactile Representation Learning in Vision-Tactile-Language-Action Models for Dexterous Manipulation
Sep 11, 2026Xiangcheng Liu, Tianhao Wu, Le Zheng +6Representation Learning Tactile-Vision-Language-Action Models
Shanghai Innovation Institute · Agibot
DeCAL: Towards Physically-Grounded Dexterous Vision-Language-Action Models via Contact-Aware Latent Co-Imagination
Sep 8, 2026Yankai Fu, Ning Chen, Junkai Zhao +5Contact-Rich Robotic Manipulation Visuo-Tactile Representation Learning
State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University · Beijing Academy of Artificial Intelligence
TacForcing: Streaming Action Generation with Execution-Time Tactile Feedback
Aug 26, 2026Jianbo Zhou, Boyuan Zhao, Yuzheng Zhang +9Contact-Rich Robotic Manipulation Tactile Sensing for Robotic Manipulation
School of Computer Science, SJTU · SCUT · ECUST +5
ViTaR: Visuo-Tactile Residual Adaptation for Foundation VLA Manipulation
Aug 16, 2026Yi Wang, Renjun Wu, Jinyan Liu +1Contact-Rich Robotic Manipulation Tactile-Vision-Language-Action Models
Beijing Institute of Technology
τ: Learning Touch-Augmented Vision-Language-Action Models from Future Visual Supervision
Jul 27, 2026Ning Cheng, Jinan Xu, Wanlin Li +5Visuo-Tactile Representation Learning Vision-Language-Action Models
Beijing Jiaotong University · Beijing Institute for General Artificial Intelligence
$N_0$ -VTLA: Scaling Vision-Tactile-Language-Action Model with Latent Tactile Tokens
Jul 26, 2026NeoteAI Team, Fudan TEAI TeamTactile-Vision-Language-Action Models Long-Horizon Robotic Manipulation
NeoteAI Team · Fudan TEAI Team
Representation-Aligned Tactile Grounding for Contact-Rich Robotic Manipulation
Jul 16, 2026Ruilin Chen, Jingkai Jia, Tong Yang +8Contact-Rich Robotic Manipulation Visuo-Tactile Representation Learning
Shanghai Key Lab of Intelligent Information Processing, College of Computer Science and Artificial Intelligence, Fudan University · College of Intelligent Robotics and Advanced Manufacturing, Fudan University · TeleAl, China Telecom +2
UniTacVLA: Unified Tactile Understanding and Prediction in Vision Language Action Models
Jun 30, 2026Xidong Zhang, Yichi Zhang, Jiaxin Shi +5Visual-to-Tactile Prediction Contact-Rich Robotic Manipulation
Harbin Institute of Technology · Great Bay University · Daimon Robotics +3
TAP-VLA: Tactile Annotation Prompting for Vision Language Action Models
Jun 27, 2026Mark Van der Merwe, Mohamad Louai Shehab, Jayjun Lee +4Vision-Language-Action Models Tactile Sensing for Robotic Manipulation
Robotics Department, University of Michigan · Computer Science and Engineering Department, University of Michigan
T-Rex: Tactile-Reactive Dexterous Manipulation
Jun 15, 2026Dantong Niu, Zhuoyang Liu, Zekai Wang +31Visuo-Tactile Representation Learning Tactile Sensing for Robotic Manipulation
UC Berkeley · NVIDIA · La Sapienza University +3
TacCoRL: Integrating Tactile Feedback into VLA via Simulation
Jun 10, 2026Siyu Ma, Yuqi Liang, Chang Yu +5RL for Robotics Tactile-Vision-Language-Action Models
University of California, Los Angeles · University of California, San Diego · 4Peking University +1
VitaTouch: Property-Aware Vision-Tactile-Language Model for Robotic Quality Inspection in Manufacturing
Apr 2, 2026Junyi Zong, Qingxuan Jia, Meixian Shi +5Tactile-Vision-Language-Action Models Robotic Anomaly Detection
School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China. · Zhongguancun Academy, Beijing 100094, China. · School of Automation, Beijing Institute of Technology, Beijing 100081, China. +2
HapticVLA: Contact-Rich Manipulation via Vision-Language-Action Model without Inference-Time Tactile Sensing
Mar 16, 2026Konstantin Gubernatorov, Mikhail Sannikov, Ilya Mikhalchuk +7Robotic Manipulation Tactile-Vision-Language-Action Models
Intelligent Space Robotics Laboratory, Skolkovo Institute of Science and Technology, Moscow, Russia.
Tactile Modality Fusion for Vision-Language-Action Models
Mar 15, 2026Charlotte Morissette, Amin Abyaneh, Wei-Di Chang +5Contact-Rich Robotic Manipulation Vision-Language-Action Models
McGill University, CAN · Mila - Québec AI Institute, CAN · NVIDIA, USA
TacVLA: Contact-Aware Tactile Fusion for Robust Vision-Language-Action Manipulation
Mar 13, 2026Kaidi Zhang, Heng Zhang, Zhengtong Xu +7Tactile-Vision-Language-Action Models Contact-Rich Robotic Manipulation
Kaidi, Heng, Zhengtong, Zhiyuan, Prince, Xiang, Xiaojing, Yuhao, and Yu are with the Edwardson School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA · Human-Robot Interfaces and Interaction Lab, Istituto Italiano di Tecnologia, Genova, Italy. · Ph.D. program of national interest in Robotics and Intelligent Machines (DRIM) and Università di Genova, Genoa, Italy. +1

Oct 20, 2026J/K move · Enter open · S save

T-WLA: Bridging Slow Vision and Fast Touch

Kaichen Zhou, Yuzhen Chen, Hannah Yao, Chonghe Jiang+13

Massachusetts Institute of Technology · Harvard University · University of California, Davis+1

Tactile-Vision-Language-Action Models Contact-Rich Robotic Manipulation Robotic Manipulation Tactile Sensing for Robotic Manipulation

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In contact-rich manipulation, contact conditions can change before a visual policy updates its action plan. Recomputing the plan through the visual policy adds latency, while tactile feedback alone does not specify how the ongoing motion should be revised for the task. We introduce T-WLA, a world-language-action architecture that uses shared visual memory to guide both action generation and tactile correction. At each visual update, the visual branch integrates the current image, task instruction, and retrieved history into a visual memory that conditions base-action generation. The same memory is cached for a lightweight tactile editor, which combines it with the active action chunk and incoming touch to predict residual corrections to unexecuted actions without rerunning the visual branch. Future-image and future-pressure prediction provide training-only supervision, encouraging the visual memory and tactile features to capture interaction dynamics relevant to action generation and correction. We evaluate T-WLA on tactile-conditioned hand-motion prediction using EgoTouch and Tachin, and on four real-world dexterous manipulation tasks. T-WLA reduces finger-joint MPJPE by 30% relative to the strongest reported baseline and achieves an average success rate of approximately 50.0% across real-robot manipulation tasks. Videos and code are available at https://anonymous-submission-20.github.io/T-WLA.github.io/.