Papers by Panatchakorn Anantaprayoon
Evaluating Gender Bias of Pre-trained Language Models in Natural Language Inference by Considering All Labels (2024.lrec-main)
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| Challenge: | Existing methods to evaluate gender bias in PLMs focus on one label out of three labels, such as neutral. |
| Approach: | They propose a bias evaluation method for PLMs that considers all the three labels of NLI task and then defines a measure based on the corresponding label output. |
| Outcome: | The proposed method can distinguish biased, incorrect inferences from non-biased incorrect infertility better than baseline, resulting in a more accurate bias evaluation. |