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Informed Data Selection Strategies for Few-Shot Learning on Imbalanced Data
Alcoforado, Alexandre; Okamura, Lucas; Ferraz, Thomas; Campos Fama, Israel; Dias Bueno, Bárbara; Veloso, Bruno Miguel; Reali Costa, Anna HelenaAcquiring high-quality annotated data remains one of the most significant challenges in Natural Language Processing (NLP), especially for supervised learning approaches. In scenarios where pre-existing labeled data is unavailable, common solutions like crowdsourcing and zero-shot approaches often fall short, suffering from limitations such as the need for large datasets and a lack of guarantees regarding annota...
Data: 2025
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Origem: Linguamática