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@du_yilun
Assistant Professor at Harvard @KempnerInst + CS. PhD @MIT_CSAIL, BS MIT. Generative Models, Compositionality, Embodied Agents, Robot Learning.
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The ScaleMAS announcement says agents publish findings in a shared database and link to work they build on.
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A post describing RAX reports a 78.3% RoboDojo result, versus 24.9% for the prior state of the art.
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The researchers say the method pairs reconstruction pretraining with distributional post-training, without relying on a diffusion teacher.
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A user highlights NeurIPS work on estimating SE(3) transforms from video and suggests a possible robotics use.
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The SIMPACT project describes an agent that proposes rough actions, tests them in simulation and refines them before a robot executes them in the real world.
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A post links to the paper “Training Object Permanence in World Models” on Hugging Face.
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Harvard assistant professor outlines his introduction of Comet as compositional energy concepts.
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Harvard assistant professor states COMET enables wider research adoption.
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Researchers on X compare the new Explorative Modeling paper to earlier IMLE methods in algorithms, loss, and motivation.
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Side-by-side excerpts highlight similar mode forcing sections in XM and CHIMLE papers.
