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Researchers from CMU and Bosch Center for AI introduced the Humanoid Transformer with Touch Dreaming (HTD) model, which uses tactile signal prediction to improve humanoid robot manipulation, achieving a 90.9% higher average success rate over the ACT baseline across five real-world tasks.