Unverified50% confidenceFactExact time
A forward pass refers to a complete process in which input data flows from the first layer of the network to the last layer, passing through the computation of each layer in turn to produce an output.
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10/20/2026
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Unverified前向传播（forward pass）描述数据从输入层经过每一层网络变换最终输出预测结果的完整流程79% similarUnverifiedA forward pass is the process of a neural network computing once completely from the input layer to the output layer; an autoregressive language model needs N forward passes to generate N tokens, with latency growing linearly with output length; a classifier-style model needs only one forward pass.71% similarUnverifiedLayer attribution analysis is a technique for quantifying the contribution of each layer in a network to the final output, and common approaches include gradient-based attribution, activation patching, or ablation experiments.69% similarUnverified输出生成是严格串行的自回归过程，每生成一个token都需要一次完整的模型前向传播68% similarUnverifiedAutoregressive models work by taking the output of the previous step as the input for the next step, generating sequences incrementally.68% similar
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