A Light-Weight Strategy for Restraining Gender Biases in Neural Rankers

Amin Bigdeli, Negar Arabzadeh, Shirin Seyedsalehi, Morteza Zihayat, Ebrahim Bagheri
January 2022

Abstract

This paper presents a light-weight strategy for restraining gender biases in neural rankers, providing efficient bias mitigation approaches for information retrieval systems.

Type
Conference paper
Publication
European Conference on Information Retrieval (ECIR)

This work introduces efficient light-weight approaches for mitigating gender biases in neural ranking systems.

Gender Bias Neural Rankers Light-Weight Methods Bias Mitigation Information Retrieval
Morteza Zihayat
Morteza Zihayat
Principal Investigator

Dr. Morteza Zihayat is an Assistant Professor in the School of Information Technology Management at Toronto Metropolitan University and the Director of the Human-Centered Machine Intelligence Lab.