https://uma-manipulation.github.io/

Contrastive Action-Image Pre-training for Visuomotor Control

GPC: Large-Scale Generative Pretraining for Transferable Motor Control

VLK: Learning Humanoid Loco-Manipulation from Synthetic Interactions in Reconstructed Scenes

TEXEDO : Test Time Scaling for Controller-aware Language-conditioned Humano

MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control

Lifting Embodied World Models for Planning and Control

Autoregressive Diffusion with Hybrid Representation for Interactive Human Motion Generation

InterPet4D: A Multimodal 4D Human-Pet Interaction Dataset for Pet Motion Generation

WristMimic: Full-Body Humanoid Control with Wrist-Guided Manipulation

SceneBot: Contact-Prompted General Humanoid Whole Body Tracking with Scene-Interaction

MotionWAM: Towards Foundation World Action Models for Real-Time Humanoid Loco-Manipulation

OpenHLM: An Empirical Recipe for Whole-Body Humanoid Loco-Manipulation

Scaling Behavior Foundation Model for Humanoid Robots

EgoHTR: Egocentric 4D Demonstrations of Human Terrain Traversal

Perceptive Behavior Foundation Model: Adapting Human Motion Priors to Robot-Centric Terrain