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Updated: Jan 10, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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收获LLM修剪的果实:朝着小型语言模型,以实现高效的非编码变体效应预测

Megha Hegde1, Jean-Christophe Nebel2, Farzana Rahman1

  • 1School of Computer Science and Mathematics, Kingston University, London KT1 2EE, UK.

Genes
|November 27, 2025
PubMed
概括

层修剪使大型基因组语言模型更有效地进行变异预测. 删除冗余层可以降低计算需求,而不会牺牲准确性,改善非编码变体解释.

关键词:
深度学习是一种深度学习.大型语言模型没有编码的DNA.小语言模型小语言模型变体效应预测变体效应预测

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