Papers by Enamul Hassan

2 papers
BanStereoSet: A Dataset to Measure Stereotypical Social Biases in LLMs for Bangla (2025.findings-acl)

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Challenge: ***BanStereoSet*** is a dataset designed to evaluate stereotypical social biases in multilingual LLMs for the Bangla language.
Approach: They propose to localize the content from StereoSet, IndiBias, and kamruzzaman-etal's datasets to capture biases prevalent within the Bangla language.
Outcome: The proposed dataset consists of 1,194 sentences spanning 9 categories of bias: race, profession, gender, ageism, beauty, beauty in profession, region, caste, and religion.
EmoNoBa: A Dataset for Analyzing Fine-Grained Emotions on Noisy Bangla Texts (2022.aacl-short)

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Challenge: EmoNoBa is a dataset for fine-grained emotion detection on Bangla text . it is based on 22698 comments from social media sites on 12 domains .
Approach: They propose a manually annotated dataset of 22,698 Bangla comments from social media sites on 12 different domains to use for fine-grained emotion detection.
Outcome: The proposed dataset of 22,698 public comments on 12 domains shows that hand-crafted features perform better than neural networks and pre-trained language models.

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