English(EN) Demystifying Manifold Constraints in LLM Pre-training

新的MACRO优化器揭秘大语言模型预训练约束

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-07 04:00

研究人员推出了一种新颖的优化框架MACRO，旨在揭秘大语言模型预训练中流形约束的作用。该框架在理论上将权重正则化与RMS归一化和解耦权重衰减等其他稳定技术分离开来。在大规模大语言模型架构上的实证评估表明，MACRO在保持精确黎曼优化的理论保证的同时，取得了具有竞争力的性能。 AI

影响引入了一个新的优化框架，可能会提高大语言模型的训练稳定性和性能。

排序理由这是一篇详细介绍大语言模型预训练新优化框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Kang An, Jiaxiang Li, Donald Goldfarb, Shiqian Ma · 2026-05-07 04:00

揭秘LLM预训练中的流形约束

arXiv:2605.04418v1 Announce Type: new Abstract: The empirical success of large language model (LLM) pre-training relies heavily on heuristic stabilization techniques, such as explicit normalization layers and weight decay. While recent constrained optimization approaches that exp…