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optimize large-scale distributed training frameworks (e.g., data parallelism, tensor parallelism, pipeline parallelism). Develop high-performance inference engines, improving latency, throughput, and memory
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parallel, we focus on engineering metamaterial structures at subwavelength scales to achieve unprecedented electromagnetic, acoustic, or mechanical properties not found in natural materials. We
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-Based Generative Models: How can we fundamentally redesign generation processes for superior efficiency, controllability, and quality? We are exploring diffusion models, flow-matching, and other parallel
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