Mahammed Kamruzzaman

According to our database1, Mahammed Kamruzzaman authored at least 13 papers between 2023 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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PhD thesis 
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Bibliography

2025
From Anger to Joy: How Nationality Personas Shape Emotion Attribution in Large Language Models.
CoRR, June, 2025

The Impact of Disability Disclosure on Fairness and Bias in LLM-Driven Candidate Selection.
Proceedings of the 38th International Florida Artificial Intelligence Research Society Conference, 2025

BanStereoSet: A Dataset to Measure Stereotypical Social Biases in LLMs for Bangla.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

The Impact of Name Age Perception on Job Recommendations in LLMs.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

Investigating and Mitigating Undesirable Biases in Large Language Models.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
"A Woman is More Culturally Knowledgeable than A Man?": The Effect of Personas on Cultural Norm Interpretation in LLMs.
CoRR, 2024

"Global is Good, Local is Bad?": Understanding Brand Bias in LLMs.
CoRR, 2024

Exploring Changes in Nation Perception with Nationality-Assigned Personas in LLMs.
CoRR, 2024

Prompting Techniques for Reducing Social Bias in LLMs through System 1 and System 2 Cognitive Processes.
CoRR, 2024

"Global is Good, Local is Bad?": Understanding Brand Bias in LLMs.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Investigating Subtler Biases in LLMs: Ageism, Beauty, Institutional, and Nationality Bias in Generative Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
BanMANI: A Dataset to Identify Manipulated Social Media News in Bangla.
CoRR, 2023

Efficient Sentiment Analysis: A Resource-Aware Evaluation of Feature Extraction Techniques, Ensembling, and Deep Learning Models.
CoRR, 2023


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