新闻
MuonGS: Pretraining LLMs with Relaxed Weight-Norm Control
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- MuonGS, a new optimizer for LLM pretraining, uses Gram-Schmidt projection to control weight growth while allowing more flexible norm constraints than prior Muon variants.
- 为何重要
- Matters for engineers optimizing large language model training who want faster convergence and better long-horizon performance with existing hardware budgets.
- 注意
- Paper shows fifteen percent token-equivalent speedup on tested models, but real-world gains depend on implementation details and may not generalize to all architectures or scales.
- llm
- language model
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