Publications

You can also find my articles on my Google Scholar profile.

Conference Papers

ChitroJera: A Regionally Relevant Visual Question Answering Dataset for Bangla

Published in ECML PKDD, 2025

Authors:Deeparghya Dutta Barua, Md Sakib Ul Rahman Sourove, Md Fahim, Fabiha Haider, Fariha Tanjim Shifat, Md Tasmim Rahman Adib, Anam Borhan Uddin, Md Farhan Ishmam, Md Farhad Alam

In this research project, we explored the performance of Large Vision-Language Models on Bangla Visual Question Answering (VQA) tasks. Due to the lack of existing datasets in this domain, we developed a novel dataset specifically tailored for Bangla VQA. We conducted a series of experiments from multiple perspectives to effectively address our research objectives.

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BanTH: A Multi-label Hate Speech Detection Dataset for Transliterated Bangla

Published in NAACL Findings, 2025

Authors:Fabiha Haider, Fariha Tanjim Shifat, Md Farhan Ishmam, Deeparghya Dutta Barua, Md Sakib Ul Rahman Sourove, Md Fahim, Md Farhad Alam

As transliterated Bangla (Banglish) is one of the most common forms of online communication, detecting hate content in this form is crucial. We present BANTH, the first multi-label transliterated Bangla hate speech dataset. We also propose a novel translation-based prompting strategy with LLMs achieving superior performance over existing baselines and paving the way for more effective hate speech detection in underrepresented languages.

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BanglaTLit: A Benchmark Dataset for Back-Transliteration of Romanized Bangla

Published in EMNLP Findings, 2024

Authors:Md Fahim, Fariha Tanjim Shifat, Fabiha Haider, Deeparghya Dutta Barua, Md Sakib Ul Rahman Sourove, Md Farhan Ishmam, Md Farhad Alam

To tackle Romanized Bangla (commonly known as Banglish), the most widely used text form on social media, we introduce BanglaTLit and BanglaTLit-PT — two large-scale datasets that fuel state-of-the-art performance in Banglish NLP. Our novel back-transliteration techniques and further-pretrained encoders unlock the full potential of this noisy yet rich linguistic resource.

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Workshops

Robustness of LLMs to Transliteration Perturbations in Bangla

Published in BLP-Workshop, 2025

Authors:Fabiha Haider, Md Farhan Ishmam, Fariha Tanjim Shifat, Md Tasmim Rahman Adib, Md Fahim, Md Farhad Alam Bhuiyan

Bangla text online often mixes Bangla script with Romanized Bangla. To handle this, language models need to be able to understand this script mixing. In this work, we test how well current LLMs and Bangla models handle different types of transliteration-based changes. We create mixed-script versions of Bangla data by replacing some words, sentences, or important keywords with their transliterated forms. Our experiments show weaknesses and interesting behaviors in these models, highlighting the need to improve robustness for real-world use.

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Penta-nlp at EXIST 2024 Task 1-3: Sexism Identification, Source Intention, Sexism Categorization In Tweets

Published in EXIST, 2024

Authors:Fariha Tanjim Shifat, Fabiha Haider, Md Sakib Ul Rahman Sourove, Deeparghya Dutta Barua, Md Farhan Ishmam, Md Fahim and Farhad Alam Bhuiyan

Automated detection of sexist content is vital to curb harmful stereotypes on social media. This study explores various NLP techniques and attention mechanisms to identify and flag sexist tweets, using a large multilingual dataset to improve moderation effectiveness at scale.

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Penta ML at EXIST 2024: Tagging Sexism in Online Multimodal Content With Attention-enhanced Modal Context

Published in EXIST, 2024

Authors:Deeparghya Dutta Barua, Md Sakib Ul Rahman Sourove, Fabiha Haider, Fariha Tanjim Shifat, Md Farhan Ishmam, Md Fahim and Farhad Alam Bhuiyan

Effective content moderation requires automated systems that understand nuanced, multimodal, and multilingual online content. This study explores an attention-based approach to better balance textual and visual cues, improving performance in identifying sexism and other complex labels.

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GitHub Repository