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EmbodiedVAE: Disentangled Video VAE for Efficient and Controllable Embodied Manipulation
Jiayi Luo, Hanxin Zhu, Chen Gao +5
Latent diffusion models (LDMs) have recently significantly advanced embodied learning in constructing powerful embodied manipulation world models. However, despite the remarkable p…
DeformGen: Dynamics-Based Topology Augmentation for Deformable Manipulation Policy Learning
Zili Lin, Wenyao Zhang, Yuyang Zhang +9
Demonstration augmentation is proposed for cost-efficient data acquisition, but existing methods are fundamentally limited in deformable manipulation due to two challenges: (1) the…
MemCompiler: Compile, Don't Inject -- State-Conditioned Memory for Embodied Agents
Xin Ding, Xinrui Wang, Yifan Yang +9
Existing memory systems for embodied agents typically inject retrieved memory as static context at episode start, a paradigm we term Ahead-of-time Monolithic Memory Injection (AMMI…
VLA-JEPA: Enhancing Vision-Language-Action Model with Latent World Model
Jingwen Sun, Wenyao Zhang, Zekun Qi +6
Pretraining Vision-Language-Action (VLA) policies on internet-scale video is appealing, yet current latent-action objectives often learn the wrong thing: they remain anchored to pi…