A Novel Information-Theoretic Objective to Disentangle Representations for Fair Classification

21 October 2023

Papers citing "A Novel Information-Theoretic Objective to Disentangle Representations for Fair Classification"

7 / 7 papers shown

Title
Conditional Supervised Contrastive Learning for Fair Text Classification Jianfeng Chi Will Shand Yaodong Yu Kai-Wei Chang Han Zhao Yuan Tian FaML 46 14 0 23 May 2022
Beam Search with Bidirectional Strategies for Neural Response Generation Pierre Colombo Chouchang Yang Giovanna Varni Chloé Clavel 39 13 0 07 Oct 2021
Contrastive Learning for Fair Representations Aili Shen Xudong Han Trevor Cohn Timothy Baldwin Lea Frermann FaML 39 33 0 22 Sep 2021
Adversarial Scrubbing of Demographic Information for Text Classification Somnath Basu Roy Chowdhury Sayan Ghosh Yiyuan Li Junier B. Oliva Shashank Srivastava Snigdha Chaturvedi 42 14 0 17 Sep 2021
Mitigating Language-Dependent Ethnic Bias in BERT Jaimeen Ahn Alice H. Oh 136 91 0 13 Sep 2021
A Primer on Contrastive Pretraining in Language Processing: Methods, Lessons Learned and Perspectives Nils Rethmeier Isabelle Augenstein SSL VLM 87 90 0 25 Feb 2021
CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding Yanru Qu Dinghan Shen Yelong Shen Sandra Sajeev Jiawei Han Weizhu Chen 132 66 0 16 Oct 2020