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cs.LG2025
Objective Value Change and Shape-Based Accelerated Optimization for the Neural Network Approximation
Pengcheng Xie, Zihao Zhou, Zijian Zhou
This paper introduce a novel metric of an objective function f, we say VC (value change) to measure the difficulty and approximation affection when conducting an neural network app…
cs.LG2025
Amber Pruner: Leveraging N:M Activation Sparsity for Efficient Prefill in Large Language Models
Tai An, Ruwu Cai, Yanzhe Zhang +6
In the era of large language models (LLMs), N:M sparsity has emerged as a structured compression technique critical for accelerating inference. While prior work has primarily focus…