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cs.RO2026
Self-Labeled Preference Transfer for Steerable Robot Manipulation
Kaiwen Hong, Shaoting Peng, Xiangyu Zeng +6
Vision-language-action (VLA) policies can learn to follow execution preferences, such as where to grasp an object or how to move around an obstacle, from demonstrations annotated w…
cs.RO2026
VTAM: Efficient Visuo-Tactile World-Action Models for Contact-Rich Manipulation without Tactile Pretraining
Haoran Yuan, Weigang Yi, Zhenyu Zhang +11
Tactile vision-language-action models (VLAs) and tactile world-action models (WAMs) are a promising new paradigm for contact-rich manipulation, but existing models either underutil…