2 papers
cs.CL2026
Learning Sexism Detection Using Multi-Agent Perspectivist Preference Optimization
Hadi Mohammadi, Tina Shahedi, Robert A. Bagheri +2
When people label text for sexism, they often disagree, and not because some of them are wrong: they genuinely perceive sexism differently. Most NLP systems discard this disagreeme…
cs.CL2025
Assessing the Reliability of LLMs Annotations in the Context of Demographic Bias and Model Explanation
Hadi Mohammadi, Tina Shahedi, Pablo Mosteiro +3
Understanding the sources of variability in annotations is crucial for developing fair NLP systems, especially for tasks like sexism detection where demographic bias is a concern.…