Papers by Lina Conti

1 papers
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.

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