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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 Helena

Acquiring 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...

Date: 2025   |   Origin: Linguamática

DEBACER: a method for slicing moderated debates

Ferraz, Thomas Palmeira; Alcoforado, Alexandre; Bustos, Enzo; Oliveira, André Seidel; Gerber, Rodrigo; Müller, Naíde; d’Almeida, André Corrêa

Subjects change frequently in moderated debates with several participants, such as in parliamentary sessions, electoral debates, and trials. Partitioning a debate into blocks with the same subject is essential for understanding. Often a moderator is responsible for defining when a new block begins so that the task of automatically partitioning a moderated debate can focus solely on the moderator's behavior. In ...


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