AB
A.M.A. Balayn
3 records found
1
Authored
On the fairness of crowdsourced training data and Machine Learning models for the prediction of subjective properties. The case of sentence toxicity
To be or not to be #$@&%*! toxic? To be or not to be fair?
Training machine learning (ML) models for natural language processing usually requires lots of data that is often acquired through crowdsourcing. In crowdsourcing, crowd workers annotate data samples according to one or more properties, such as the sentiment of a sentence, the vi
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Contributed
In recent years, there has been a growing interest among researchers in the explainability, fairness, and robustness of Computer Vision models. While studies have explored the usability of these models for end users, limited research has delved into the challenges and requirement
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We introduce Swipe for Science, a single-player mobile game designed for collecting discriminative evidence from crowds. When people play this game, we collect data about how certain concepts are associated with different contexts, which is valuable knowledge for machine learning
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