Papers by Sebastian Cifuentes
A Study of Nationality Bias in Names and Perplexity using Off-the-Shelf Affect-related Tweet Classifiers (2024.emnlp-main)
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| Challenge: | Recent research shows that named entities influence PLMs in many applications. |
| Approach: | They propose a method to quantify biases associated with named entities from various countries using Twitter data instead of templates or specific datasets. |
| Outcome: | The proposed method shows positive biases related to the language spoken in a country across all classifiers. |
Are Text Classifiers Xenophobic? A Country-Oriented Bias Detection Method with Least Confounding Variables (2024.lrec-main)
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| Challenge: | Existing methods for detecting biases are biased because of confounding variables . authors propose a method to detect the biased classifier on any type of unlabeled data . |
| Approach: | They propose a method to detect biases of a specific fine-tuned classifier on unlabeled data. |
| Outcome: | The proposed method detects biases on unlabeled data on named entity perturbations . it uses name-entity recognition on target-domain data and morphosynctactically different languages spoken in relation to countries of the target groups . |