Papers by Abul Hasan
MemeIntel: Explainable Detection of Propagandistic and Hateful Memes (2025.emnlp-main)
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| Challenge: | Existing methods for label detection and explanation generation have been limited in understanding complex issues . identifying propaganda and hate in memes is essential for combating misinformation and minimizing harm . |
| Approach: | They propose an explanation-enhanced dataset for propaganda memes in Arabic and hateful memes on English to solve these tasks. |
| Outcome: | The proposed model outperforms the current state-of-the-art in label detection and explanation generation. |
Adverse Event Extraction from Discharge Summaries: A New Dataset, Annotation Scheme, and Initial Findings (2025.acl-long)
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Imane Guellil, Salomé Andres, Atul Anand, Bruce Guthrie, Huayu Zhang, Abul Hasan, Honghan Wu, Beatrice Alex
| Challenge: | Existing resources for AE extraction are limited due to complexity, variability, and ambiguity of clinical narratives. |
| Approach: | They present a manually annotated corpus for Adverse Event (AE) extraction from discharge summaries of elderly patients. |
| Outcome: | The proposed model performs well on coarse-grained extraction, but drops notably for rare events and complex attributes. |
ArMeme: Propagandistic Content in Arabic Memes (2024.emnlp-main)
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| Challenge: | a lack of media literacy is a major factor contributing to the spread of misleading information on social media. |
| Approach: | They analyze a dataset of 6K Arabic memes with manual annotations . they propose to develop computational tools for their detection . |
| Outcome: | The proposed dataset is a first resource for Arabic multimodal research. |