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Tail events in EHR generation can be accurately modeled with a 114.2% improvement over existing methods, transforming how we approach rare disease data synthesis.
Current OmniLLMs stumble when processing real-world, long-form audio-visual content, achieving only ~35-65% accuracy on a new benchmark designed to test long-term memory and fine-grained understanding.
