English(EN) How Much Gradient Does Truncated Backprop Lose in Looped Transformers?

研究量化了循环 Transformer 中的梯度损失

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-22 04:00

一篇新的研究论文调查了截断反向传播对循环 Transformer 的影响，这是一种将单个层块重复使用多次的技术。该研究测量了仅通过最后 k 个循环反向传播所产生的梯度损失，发现损失的梯度集中在输出附近，并在微调过程中显著减少。研究还表明，用于估算训练成本的简单规则可能与直接测量梯度一样有效。 AI

影响这项研究可以为更高效的 Transformer 架构训练方法提供信息，从而可能降低计算成本。

排序理由学术论文，详细介绍了关于模型训练的特定技术发现。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Aur Shalev Merin · 2026-10-22 04:00

截断反向传播在循环 Transformer 中会损失多少梯度？

arXiv:2610.28871v1 Announce Type: new Abstract: Looped transformers reuse one block of layers many times and are often trained by backpropagating through only the last k loops. We measure how much of the weight gradient this throws away, exactly and for every k from one backward …