collaborators

5 papers

cs.CL2025

Do Large Language Models Understand Morality Across Cultures?

Hadi Mohammadi, Yasmeen F. S. S. Meijer, Efthymia Papadopoulou +1

Recent advancements in large language models (LLMs) have established them as powerful tools across numerous domains. However, persistent concerns about embedded biases, such as gen…

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.…

cs.CL2025

Explainability-Based Token Replacement on LLM-Generated Text

Hadi Mohammadi, Anastasia Giachanou, Daniel L. Oberski +1

Generative models, especially large language models (LLMs), have shown remarkable progress in producing text that appears human-like. However, they often exhibit patterns that make…

cs.AI2024

LLMs as mirrors of societal moral standards: reflection of cultural divergence and agreement across ethical topics

Mijntje Meijer, Hadi Mohammadi, Ayoub Bagheri

Large language models (LLMs) have become increasingly pivotal in various domains due the recent advancements in their performance capabilities. However, concerns persist regarding…

cs.AI2024

Large Language Models as Mirrors of Societal Moral Standards

Evi Papadopoulou, Hadi Mohammadi, Ayoub Bagheri

Prior research has demonstrated that language models can, to a limited extent, represent moral norms in a variety of cultural contexts. This research aims to replicate these findin…