Global

5 vision-language model and integrates 3D perception, visual question answering, and motion planning within a unified framework. 5-4B serves as the shared VLM, with two external modules attached:

Pixels are evidence of the physical world, not its ontology. A pixel-level observation records how the world appears at a particular moment and from a particular viewpoint, but does not directly specify what exists within it, how it is structured, or what governs its evolution.

RADAR is a generalist vision-language model trained on over 400,000 contrast-enhanced abdominal CT examinations with 15 million anatomy-aware image–text pairs, learning directly from clinical reports without manual annotation.

ParseBench is a benchmark for evaluating how well document parsing tools convert PDFs into structured output that AI agents can reliably act on.

The in-context human video generation pipeline starts from task-sampled robot trajectories that retain executable actions.

Evolving Multimodal Inference Programs: LLM-guided evolutionary search for accurate and efficient vision-language inference.

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