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Achieve state-of-the-art multimodal intent recognition by structuring semantics into progressively abstracted levels and dynamically refining representations through MLLM feedback.
A 1000x larger video reasoning dataset reveals early signs of emergent generalization, offering a new foundation for training and evaluating spatiotemporal AI.
By modeling the entire clinical phenotyping workflow, RARE-PHENIX extracts structured, ranked phenotypes that align more closely with clinician curation, potentially revolutionizing rare disease diagnosis.
