7 papers · 1 filter
CogWAM: Aligning Semantic Cognition with World Action Modeling via Event-Driven Interfaces
Sen Wang, Liu Liu, Xinjiang Wang +7
Robot policies increasingly incorporate semantic reasoning and future-world prediction, yet combining these capabilities does not guarantee that local predictions and actions remai…
InstructMove: A Text-Indispensable Benchmark for Instruction-Following Manipulation
Mengao Zhao, Ziang Li, Chaodong Huang +15
Vision-language-action (VLA) models have made general-purpose robot manipulation increasingly plausible by conditioning robot actions on natural-language instructions. A key test o…
EmbodiedGen V2: An Agentic, Simulation-Ready 3D World Engine for Embodied AI
Xinjie Wang, Liu Liu, Taojun Ding +9
We present EmbodiedGen V2, a generative 3D world engine for building executable policy-ready environments for embodied intelligence. Sim-ready 3D asset generation has advanced rapi…
NativeMEM: Native Memory Compression for Long-Horizon Robotic Manipulation
Ziye Wang, Modi Shi, Chaojun Ni +5
How can pretrained Vision-Language-Action (VLA) models retain long-horizon visual histories with high-frequency updates without sacrificing efficiency? Existing approaches rely on…
HoloBrain-0 Technical Report
Xuewu Lin, Tianwei Lin, Yun Du +12
In this work, we introduce HoloBrain-0, a comprehensive Vision-Language-Action (VLA) framework that bridges the gap between foundation model research and reliable real-world robot…
RISE: Self-Improving Robot Policy with Compositional World Model
Jiazhi Yang, Kunyang Lin, Jinwei Li +10
Despite the sustained scaling on model capacity and data acquisition, Vision-Language-Action (VLA) models remain brittle in contact-rich and dynamic manipulation tasks, where minor…
H-RDT: Human Manipulation Enhanced Bimanual Robotic Manipulation
Hongzhe Bi, Lingxuan Wu, Tianwei Lin +4
Imitation learning for robotic manipulation faces a fundamental challenge: the scarcity of large-scale, high-quality robot demonstration data. Recent robotic foundation models ofte…