Exploration and mitigation of gender bias in word embeddings from transformer-based language models

Exploration and mitigation of gender bias in word embeddings from transformer-based language models

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Detalhes bibliográficos
Principais autores: Hossain, Ariyan, Haque, Rakinul, Hannan, Khondokar Mohammad Ahanaf, Rafa, Nowreen Tarannum, Musarrat, Humayra
Outros Autores: Sadeque, Farig Yousuf
Formato: Tese
Idioma:English
Publicado em: Brac University 2024
Assuntos:
Natural Llnguage processing
Gender bias
Debiasing
Continued pretraining
Natural language processing (Computer science)
Acesso em linha:http://hdl.handle.net/10361/23457

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