Language Model-Driven Data Pruning Enables Efficient Active Learning

Active learning (AL) optimizes data labeling efficiency by selecting the most informative instances for annotation. A key component in this procedure is an acquisition function that guides the selection process and identifies the suitable instances for labeling from the unlabeled pool. However, thes...

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Hauptverfasser:	Azeemi, Abdul Hameed, Qazi, Ihsan Ayyub, Raza, Agha Ali
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computation and Language Computer Science - Learning
Online-Zugang:	Volltext bestellen
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