Gabriel Prenassi

Instance-Selection-Inspired Undersampling Strategies for Bias Reduction in Small and Large Language Models for Binary Text Classification

Skewness in imbalanced datasets affects Automatic Text Classification (ATC), leading to classifier bias toward the majority classes. This work examines undersampling methods to mitigate such bias in Small and Large Language Model (SLMs and LLMs) classifiers. Based on the limitations found in existin…