AI前沿：采样新思路，训练新方法

还在为LLM生成文本不够连贯而烦恼吗？还在为大模型训练内存消耗过大而头疼吗？这期“TAI快报”，带你深入了解AI研究的最新进展！我们精选了四篇前沿论文，为你揭秘：如何用Min-p采样让LLM在高温度下也能生成高质量文本？如何用“切分交叉熵”大幅降低大模型训练的内存消耗？如何用解耦嵌入提高多语言模型和联邦学习的效率？如何用TimeMixer++构建一个通用的时间序列分析模型？完整推介：https://mp.weixin.qq.com/s/JS_mCwTm6_bGz9nfltgLsQ在小宇宙查看该单集文稿

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AI前沿：采样新思路，训练新方法

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