Papers by Lina Conti
Using Artificial French Data to Understand the Emergence of Gender Bias in Transformer Language Models (2023.emnlp-main)
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| Challenge: | Existing studies have demonstrated the ability of neural language models to learn linguistic properties without direct supervision. |
| Approach: | They propose to use an artificial corpus generated by a PCFG to control the gender distribution in training data and determine under which conditions a model correctly captures gender information. |
| Outcome: | The proposed approach allows to control the gender distribution in training data and determine under which conditions a model correctly captures gender information or appears gender-biased. |