Debiasing should be Good and Bad: Measuring the Consistency of Debiasing Techniques in Language Models

23 May 2023

Papers citing "Debiasing should be Good and Bad: Measuring the Consistency of Debiasing Techniques in Language Models"

6 / 6 papers shown

Title
Foundation Models at Work: Fine-Tuning for Fairness in Algorithmic Hiring Buse Sibel Korkmaz Rahul Nair Elizabeth M. Daly Evangelos Anagnostopoulos Christos Varytimidis Antonio del Rio Chanona 40 0 0 13 Jan 2025
Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs Simone Balloccu Patrícia Schmidtová Mateusz Lango Ondrej Dusek SILM ELM PILM 26 158 0 06 Feb 2024
Probing for Bridging Inference in Transformer Language Models Onkar Pandit Yufang Hou 53 14 0 19 Apr 2021
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP Timo Schick Sahana Udupa Hinrich Schütze 259 374 0 28 Feb 2021
Debiasing Pre-trained Contextualised Embeddings Masahiro Kaneko Danushka Bollegala 218 138 0 23 Jan 2021
The Woman Worked as a Babysitter: On Biases in Language Generation Emily Sheng Kai-Wei Chang Premkumar Natarajan Nanyun Peng 223 618 0 03 Sep 2019