Papers by Ali Niazi

1 papers
A Comprehensive Study of Gender Bias in Chemical Named Entity Recognition Models (2024.naacl-long)

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Challenge: Chemical named entity recognition (NER) models are used in many downstream tasks, but it is unknown whether they work the same for everyone.
Approach: They develop a framework for measuring gender bias in chemical NER models . they analyze a corpus of 92,405 words with self-identified gender information from reddit .
Outcome: The proposed framework measures gender bias in chemical NER models using synthetic data and a newly annotated corpus of over 92,405 words with self-identified gender information from Reddit.

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