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Disentangling and Operationalizing AI Fairness at LinkedIn

Disentangling and Operationalizing AI Fairness at LinkedIn

30 May 2023
Joaquin Quiñonero Candela
Yuwen Wu
Brian Hsu
Sakshi Jain
Jennifer Ramos
Jon Adams
R. Hallman
Kinjal Basu
ArXivPDFHTML

Papers citing "Disentangling and Operationalizing AI Fairness at LinkedIn"

5 / 5 papers shown
Title
INFELM: In-depth Fairness Evaluation of Large Text-To-Image Models
INFELM: In-depth Fairness Evaluation of Large Text-To-Image Models
Di Jin
Xing Liu
Yu Liu
Jia Qing Yap
Andrea Wong
Adriana Crespo
Qi Lin
Zhiyuan Yin
Qiang Yan
Ryan Ye
EGVM
VLM
86
0
0
10 Jan 2025
Natural Language Processing for Human Resources: A Survey
Natural Language Processing for Human Resources: A Survey
Naoki Otani
Nikita Bhutani
Estevam R. Hruschka
VLM
35
0
0
21 Oct 2024
Fairness in Machine Learning
Fairness in Machine Learning
L. Oneto
Silvia Chiappa
FaML
233
486
0
31 Dec 2020
Improving the Fairness of Deep Generative Models without Retraining
Improving the Fairness of Deep Generative Models without Retraining
Shuhan Tan
Yujun Shen
Bolei Zhou
175
59
0
09 Dec 2020
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
185
2,082
0
24 Oct 2016
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