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Harvard University
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A shift from artifact matching to evidence-based semantic verification could redefine how we detect AI-generated videos.
Early decision-making in multimodal reasoning can cut inference time without sacrificing accuracy, thanks to a novel dual evaluation of model competencies.
Outlier-aware rotation can halve the rotation cost in quantization while maintaining state-of-the-art performance in LLMs.
This model beats clinical reports in quantitative coronary angiography, opening the door to automated, comprehensive assessment of coronary artery disease at the point of care.
