A closed-loop Minecraft agent that imagines the next second of gameplay with a video world model and decodes it into controls — no hand-written policy, no scripted primitives.
Projects
Converting the Do as I Do pipeline into training data directly usable for Vision-Language-Action models and World Action Models, bridging everyday human manipulation videos and embodied policy learning.