High-quality data is necessary for modern machine learning. However, the acquisition of
such data is difficult due to noisy and ambiguous annotations of humans. The aggregation of …

Artificial intelligence (AI) systems are trained to solve complex problems and learn to
perform specific tasks by using large volumes of data, such as prediction, classification …

Data-centric artificial intelligence (AI)(DCAI) has the potential to bring significant benefits to
society; however, it also poses significant challenges and potential risks. It is crucial to …

High-quality data is a key aspect of modern machine learning. However, labels generated
by humans suffer from issues like label noise and class ambiguities. We raise the question …

Consistently high data quality is essential for the development of novel loss functions and
architectures in the field of deep learning. The existence of such data and labels is usually …

In the field of image classification, existing methods often struggle with biased or ambiguous
data, a prevalent issue in real-world scenarios. Current strategies, including semi …

In contrast with the research of new models, little attention has been paid to the impact of low
or high-quality data feeding a dialogue system. The present paper makes the first attempt to …

In machine learning, the availability of high-quality labeled data is essential for training
accurate models. However, humans often disagree among themselves or over time when …

Consistently high data quality is essential for the development of novel loss functions and
architectures in the field of deep learning. The existence of such data and labels is usually …

Leonardo Cardia da Cruz Habilitando Anotações de Dados Autônomos: Uma Abordagem de
Aprendizado por Reforço com Humano no Loo Page 1 Leonardo Cardia da Cruz Habilitando …