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Southeast University, Ministry of Education
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CERS leverages Chain-of-Thought reasoning to enhance medical image segmentation, significantly improving accuracy in clinically challenging scenarios where visual cues alone fall short.
LLMs can achieve 2.5x higher throughput and 10.7x KV memory reduction in long-context reasoning by compressing the KV cache using trigonometric functions derived from pre-RoPE query/key vector distributions.
