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cs.RO2026
HiMem-WAM: Hierarchical Memory-Gated World Action Models for Robotic Manipulation
Xiaoquan Sun, Ruijian Zhang, Chen Cao +12
World Action Models (WAMs) have emerged as a new powerful paradigm for embodied intelligence, learning action-relevant visual dynamics that significantly enhance generalization and…
cs.CV2026
VirtueBench: Evaluating Trustworthiness under Uncertainty in Long Video Understanding
Xueqing Yu, Bohan Li, Yan Li +1
Recent Vision-Language Models (VLMs) have made remarkable progress in multimodal understanding tasks, yet their evaluation on long video understanding remains unreliable. Due to li…
cs.RO2026
AtomVLA: Scalable Post-Training for Robotic Manipulation via Predictive Latent World Models
Xiaoquan Sun, Zetian Xu, Chen Cao +9
Vision-Language-Action (VLA) models demonstrate remarkable potential for generalizable robotic manipulation. The execution of complex multi-step behaviors in VLA models can be impr…