Genie Envisioner Act 2.0 (GE-Act 2.0) is introduced, a world-action model whose trainable generative and action components are all initialized from scratch on manipulation data, and its components are jointly trained with knowledge-aligned selective optimization (KASO), which reduces mismatched supervision.
AgiBot Research Team, Ren-Hang Liu, Wen-Zhi Zhao et al.· 4 citations· ⚡1
Flow2Act is presented, a unified framework that integrates agglomerative perception with a deterministic one-step generative policy and devise a curriculum region-aware mechanism via a Spatial-Grounded State Space Duality architecture, demonstrating significant gains in policy performance, robustness to environmental p...
Sen Wang, Le Wang, Hongcheng Huo et al.· IEEE Transactions on Pattern...· 0 citations
Experiments across action-conditioned robotic manipulation, visual planning, and model-based reinforcement learning, together with action-free driving video prediction, show that SAMPO++ improves visual prediction quality while providing stronger action alignment, counterfactual accuracy, no-op residual suppression, an...
Sen Wang, Sanpin Zhou, Huaiyi Dong et al.· IEEE Transactions on Pattern...· 0 citations
A two-stage artificial intelligence system is developed that highlights predefined suspicious features, classifies images, and shows which regions influenced its prediction of malignant biliary stricture.
