most citedTLA: Tactile-Language-Action Model for Contact-Rich Manipulation

1 citations · 1 across the 7 of their papers we have counts for

collaborators

8 papers

cs.RO2026

HiTac-WAM: A Hierarchical Tactile World Action Model for Contact-Rich Robot Manipulation

Chao Xue, Chaofan Zhang, Wenxuan Ma +3

World action models jointly predict future visual observations and actions, whereas existing tactile-aware variants typically represent future touch as an image or latent stream wi…

cs.RO2026

TacPrint: A Wearable Fingertip Tactile Sensor for Human-to-Robot Contact Reproduction

Yongxi Liu, Chaofan Zhang, Xingyu Zhang +4

Human-centric data collection is emerging as a significant paradigm for robot skill acquisition, but seamlessly integrating low-cost, scalable tactile sensing systems that capture…

cs.RO2026

FeelWorld: Visuo-Tactile World Model for Hierarchical Contact Prediction and Planning

Wenxuan Ma, Chaofan Zhang, Chao Xue +4

Humans plan physical interactions by imagining the possible outcomes of candidate actions. However, existing visual world models primarily capture appearance dynamics while overloo…

cs.RO2026

FG-CLTP: Fine-Grained Contrastive Language Tactile Pretraining for Robotic Manipulation

Wenxuan Ma, Chaofan Zhang, Yinghao Cai +3

Recent advancements in integrating tactile sensing into vision-language-action (VLA) models have demonstrated transformative potential for robotic perception. However, existing tac…

cs.RO2026

DexTac: Learning Contact-aware Visuotactile Policies via Hand-by-hand Teaching

Xingyu Zhang, Chaofan Zhang, Boyue Zhang +3

For contact-intensive tasks, the ability to generate policies that produce comprehensive tactile-aware motions is essential. However, existing data collection and skill learning sy…

cs.RO2025

VTLA: Vision-Tactile-Language-Action Model with Preference Learning for Insertion Manipulation

Chaofan Zhang, Peng Hao, Xiaoge Cao +3

While vision-language models have advanced significantly, their application in language-conditioned robotic manipulation is still underexplored, especially for contact-rich tasks t…

cs.RO2025

CLTP: Contrastive Language-Tactile Pre-training for 3D Contact Geometry Understanding

Wenxuan Ma, Xiaoge Cao, Yixiang Zhang +7

Recent advancements in integrating tactile sensing with vision-language models (VLMs) have demonstrated remarkable potential for robotic multimodal perception. However, existing ta…

cs.RO2025★ 1 cited

TLA: Tactile-Language-Action Model for Contact-Rich Manipulation

Peng Hao, Chaofan Zhang, Dingzhe Li +4

Significant progress has been made in vision-language models. However, language-conditioned robotic manipulation for contact-rich tasks remains underexplored, particularly in terms…