Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification

Predicting simple function classes has been widely used as a testbed for developing theory and understanding of the trained Transformer's in-context learning (ICL) ability. In this paper, we revisit the training of Transformers on linear regression tasks, and different from all the existing lit...

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Hauptverfasser:	Liu, Shang, Cai, Zhongze, Chen, Guanting, Li, Xiaocheng
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computation and Language Computer Science - Learning Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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