Papers by Shirlyn Tang

2 papers
Mitigating Gender Bias in Natural Language Processing: Literature Review (P19-1)

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Challenge: NLP models propagate and may even amplify gender bias found in text corpora . methods to mitigate gender bias in NLP are relatively nascent .
Approach: They propose to analyze gender bias based on four forms of representation bias and discuss the advantages and drawbacks of existing gender debiasing methods.
Outcome: The proposed methods are based on four forms of representation bias and have advantages and drawbacks.
Towards Understanding Gender Bias in Relation Extraction (2020.acl-main)

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Challenge: Existing bias mitigation techniques have a negative effect on NRE, a study finds .
Approach: They create a dataset to analyze gender bias in relation extraction systems . they find that existing bias mitigation techniques have a negative effect on NRE .
Outcome: The proposed dataset analyzes gender bias in relation extraction systems using a 10% human annotated test set.

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