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cs.RO2026
TACO: TActile World Model as a Self-COrrector for Scalable Robot Policy Post-Training
Shengbang Liu, Yueru Jia, Yuyang Yan +7
Vision-Language-Action models and World Action Models have shown promising generalization in robotic manipulation but remain fragile in contact-rich tasks, where contact perturbati…
cs.RO2026
HarmoWAM: Harmonizing Generalizable and Precise Manipulation via Adaptive World Action Models
Qiuxuan Feng, Jiale Yu, Jiaming Liu +8
World Action Models (WAMs) have emerged as a promising paradigm for robot control by modeling physical dynamics. Current WAMs generally follow two paradigms: the "Imagine-then-Exec…
cs.RO2026
RoboGene: Diversity-Driven Agentic Task Generation Framework for VLA Pre-training
Yixue Zhang, Kun Wu, Zhi Gao +12
The pursuit of general-purpose robotic manipulation is hindered by the scarcity of diverse, real-world interaction data. Unlike large-scale web vision-language data, robotic data c…