Large Language Models As Evolution Strategies

Large Transformer models are capable of implementing a plethora of so-called in-context learning algorithms. These include gradient descent, classification, sequence completion, transformation, and improvement. In this work, we investigate whether large language models (LLMs), which never explicitly...

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Veröffentlicht in:	arXiv.org 2024-02
Hauptverfasser:	Lange, Robert Tjarko, Tian, Yingtao, Tang, Yujin
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Black boxes Comparative studies Context Evolutionary algorithms Large language models Machine learning Optimization Teachers Trajectory optimization
Online-Zugang:	Volltext
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