activity
20242026
collaborators

14 papers

cs.CL2026

Translating in style: An open-weight alternative to GPT-4 for culturally aligned machine translation

Thomas Rietman, Hadi Mohammadi, Robert A. Bagheri

Machine translation systems often preserve meaning but systematically flatten linguistic style, a failure that is most acute when translating into non-Western languages. The RASTA…

cs.CL2026

trajectory-judge: What Outcome-Only LLM Judges Miss on Agent Trajectories

Hadi Mohammadi

A direct test of an LLM judge of agent trajectories injects faults into correct runs and reports recall, per fault type or by whether the fault broke the environment outcome (loud)…

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.CL2026

Reliability-Aware Sexism Detection: Combining DPO with Annotator Agreement and Token-Level Confidence Scoring

Hadi Mohammadi, Shihan Wang, Masoume M. Raeissi +1

The detection of online sexism remains an open problem. Sexism detection is inherently subjective, yet most existing systems reduce multi-annotator labels to a single majority deci…

cs.CL2025

Evaluating GRPO and DPO for Faithful Chain-of-Thought Reasoning in LLMs

Hadi Mohammadi, Tamas Kozak, Anastasia Giachanou

Chain-of-thought (CoT) reasoning has emerged as a powerful technique for improving the problem-solving capabilities of large language models (LLMs), particularly for tasks requirin…

cs.CL2025

EvalMORAAL: Interpretable Chain-of-Thought and LLM-as-Judge Evaluation for Moral Alignment in Large Language Models

Hadi Mohammadi, Anastasia Giachanou, Robert A. Bagheri

We present EvalMORAAL, a transparent chain-of-thought (CoT) framework that uses two scoring methods (log-probabilities and direct ratings) plus a model-as-judge peer review to eval…

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

Exploring Cultural Variations in Moral Judgments with Large Language Models

Hadi Mohammadi, Ayoub Bagheri

Large Language Models (LLMs) have shown strong performance across many tasks, but their ability to capture culturally diverse moral values remains unclear. In this paper, we examin…

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.LG2025

Anchor-based oversampling for imbalanced tabular data via contrastive and adversarial learning

Hadi Mohammadi, Ehsan Nazerfard, Mostafa Haghir Chehreghani

Imbalanced data represent a distribution with more frequencies of one class (majority) than the other (minority). This phenomenon occurs across various domains, such as security, m…

cs.CL2025

Explainability in Practice: A Survey of Explainable NLP Across Various Domains

Hadi Mohammadi, Robert A. Bagheri, Anastasia Giachanou +1

Natural Language Processing (NLP) is now embedded in critical sectors including healthcare, finance, and customer relationship management, where models such as GPT-4o, Gemini, and…

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…