Papers by Md. Saiful Islam
Evaluating Credibility and Political Bias in LLMs for News Outlets in Bangladesh (2025.acl-srw)
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| Challenge: | Large language models (LLMs) are widely used in search engines to provide direct an-swers, while AI chatbots retrieve updated infor-mation from the web. |
| Approach: | They audit nine Large Language Models from OpenAI, Google, and Meta to assess their ability to eval-uate the credibility and political bias of the top20 most popular news outlets in Bangladesh. |
| Outcome: | The proposed models show internal consistency in credibil-ity ratings, but misalignment with human experts. |
XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages (2021.findings-acl)
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Tahmid Hasan, Abhik Bhattacharjee, Md. Saiful Islam, Kazi Mubasshir, Yuan-Fang Li, Yong-Bin Kang, M. Sohel Rahman, Rifat Shahriyar
| Challenge: | XL-Sum dataset covers 44 languages ranging from low to high-resource . Xl-SUM is highly abstractive, concise, and of high quality . |
| Approach: | They present a dataset comprising 1 million professionally annotated article-summary pairs from BBC . they fine-tune a pretrained multilingual model with XL-Sum and experiment on multilingual and lowresource tasks. |
| Outcome: | The proposed dataset is highly abstractive, concise, and of high quality . it shows higher scores on 10 languages than similar datasets compared to monolingual ones . |