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, distillation from LLMs, acceleration such as KV caching, data synthesis, utilization of external knowledge, multimodal integration, and architecture improvement. We aim for advanced research outcomes
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intelligence. Our research spans computer vision, machine learning, and natural language processing, focusing on multimodal learning, data fusion, spatial-temporal modeling, and vision–language models. We study
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, including phase transitions, nonlinear dynamics, morphogenesis, evolution, and chromatin physics. We tackle these questions from fresh angles, using everything from physics and machine learning to long-term
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information science) as well as applied sciences utilizing quantum computers. (6) Integration of information theory, mathematical modeling and machine learning and their application to medical science problems