Gender Bias in Word Embeddings: A Comprehensive Analysis of Frequency, Syntax, and Semantics

7 June 2022

Papers citing "Gender Bias in Word Embeddings: A Comprehensive Analysis of Frequency, Syntax, and Semantics"

6 / 6 papers shown

Title
ConFit: Improving Resume-Job Matching using Data Augmentation and Contrastive Learning Xiao Yu Jinzhong Zhang Zhou Yu 32 1 0 29 Jan 2024
Semantic and Expressive Variation in Image Captions Across Languages Andre Ye Sebastin Santy Jena D. Hwang Amy X. Zhang Ranjay Krishna VLM 48 3 0 22 Oct 2023
ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages Sourojit Ghosh Aylin Caliskan 33 69 0 17 May 2023
Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models Robert Wolfe Aylin Caliskan 85 51 0 01 Oct 2021
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection Dominik Schlechtweg Barbara McGillivray Simon Hengchen Haim Dubossarsky Nina Tahmasebi 143 236 0 22 Jul 2020
Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation Tianlu Wang Xi Victoria Lin Nazneen Rajani Bryan McCann Vicente Ordonez Caimng Xiong CVBM 151 54 0 03 May 2020