{
  "abstract": "The present disclosure provides a system for generating motor control commands for a humanoid robot, comprising an alpha model with over 1 billion parameters that processes visual observations and language instructions at a first frequency to generate contextual embeddings, and a beta model operating at a higher second frequency. The beta model includes an embodiment-specific state encoder projecting robot state information into a shared embedding space, a diffusion transformer module generating denoised action sequences through iterative flow-matching that cross-attends to the alpha model's contextual embeddings, and an embodiment-specific action decoder converting denoised sequences into motor control commands. The beta model generates action chunks comprising future action sequences over a predetermined time horizon in a single inference step, with the complete system having less than 5 billion parameters.",
  "assignees": [
    "FIGURE AI INC"
  ],
  "authors": [
    "AHN MICHAEL",
    "LYNCH COREY",
    "MIGIMATSU TOKI"
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  "published_at": "2026-09-15T19:10:04.376220Z",
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  "source_date": "2026-03-12",
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  "supersedes": null,
  "title": "Bipedal action model for humanoid robot",
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