公开(公告)号：US12073178B2

公开(公告)日：2024-08-27

申请号：US17586504

申请日：2022-01-27

Applicant: salesforce.com, inc.

Inventor： Zahra Fatemi ,  Caiming Xiong ,  Wenhao Liu ,  Chen Xing

IPC: G06F40/279 ,  G06F40/35 ,  G06F40/56 ,  G06N3/045 ,  G06N3/08

CPC classification number: G06F40/279 ,  G06F40/35 ,  G06F40/56 ,  G06N3/045 ,  G06N3/08

Abstract: Embodiments are directed to a training framework for reducing gender bias in a pre-trained language model. To reduce gender bias a gender neutral dataset is generated. Next, parameters of the pre-trained language model are frozen and do not change during a subsequent training phase. As all the pre-trained parameters are frozen, forgetting of information from the original training data is minimized. New parameters are added to the language model. The new parameters may be associated with gender related terms, such as profession names. In a subsequent training phase the new parameters of the language model are trained using a gender neutral dataset.