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NGBA: A New Method for Training Large Language Models Without Backpropagation

NGBA (No-Backprop Gradient Accumulation) is a groundbreaking neural network training technique. By eliminating the inter-layer backpropagation chain rule, it enables parallel and independent updates of each layer in residual networks, significantly improving training efficiency and solving the gradient vanishing problem.

NGBANo-Backprop梯度累积大语言模型残差网络并行训练梯度消失机器学习深度学习优化
Published 2026-06-15 10:44Recent activity 2026-06-15 10:47Estimated read 1 min
NGBA: A New Method for Training Large Language Models Without Backpropagation
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导读 / 主楼:NGBA: A New Method for Training Large Language Models Without Backpropagation

Introduction / Main Post: NGBA: A New Method for Training Large Language Models Without Backpropagation

NGBA (No-Backprop Gradient Accumulation) is a groundbreaking neural network training technique. By eliminating the inter-layer backpropagation chain rule, it enables parallel and independent updates of each layer in residual networks, significantly improving training efficiency and solving the gradient vanishing problem.