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

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

23 May 2023
Robert D Morabito
Jad Kabbara
Ali Emami
ArXiv (abs)PDFHTML

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

5 / 5 papers shown
Title
Paying Alignment Tax with Contrastive Learning
Paying Alignment Tax with Contrastive Learning
Buse Sibel Korkmaz
Rahul Nair
Elizabeth M. Daly
Antonio del Rio Chanona
79
0
0
25 May 2025
Foundation Models at Work: Fine-Tuning for Fairness in Algorithmic Hiring
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
80
0
0
13 Jan 2025
'Since Lawyers are Males..': Examining Implicit Gender Bias in Hindi
  Language Generation by LLMs
'Since Lawyers are Males..': Examining Implicit Gender Bias in Hindi Language Generation by LLMs
Ishika Joshi
Ishita Gupta
Adrita Dey
Tapan Parikh
AI4CE
71
2
0
20 Sep 2024
Pitfalls of Conversational LLMs on News Debiasing
Pitfalls of Conversational LLMs on News Debiasing
Ipek Baris Schlicht
Defne Altiok
Maryanne Taouk
Lucie Flek
95
4
0
09 Apr 2024
Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in
  Closed-Source LLMs
Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs
Simone Balloccu
Patrícia Schmidtová
Mateusz Lango
Ondrej Dusek
SILMELMPILM
123
181
0
06 Feb 2024
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