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@inproceedings{bayan2026can,
title = {Can Thinking Models Think to Detect Hateful Memes?},
author = {Bayan Kmainasi, Mohamed and Kutlu, Mucahid and Ezzat Shahroor, Ali and Hasnat, Abul and Alam, Firoj},
booktitle = {Proceedings of the Fourth International Workshop on Multimodal Content Analysis for Social Good},
address = {Dubai, United Arab Emirates},
publisher = {Association for Computing Machinery},
year = {2026},
note = {Co-located with The Web Conference 2026},
url={https://arxiv.org/pdf/2603.01225},
}
@article{alam2026critisense,
title = {{CritiSense}: Critical Digital Literacy and Resilience Against Misinformation},
author = {Firoj Alam and Fatema Ahmad and Ali Ezzat Shahroor and Mohamed Bayan Kmainasi and Elisa Sartori and Giovanni Da San Martino and Abul Hasnat and Raian Ali},
journal = {arXiv preprint arXiv:2603.16672},
year = {2026},
url = {https://arxiv.org/abs/2603.16672},
}
@inproceedings{abbas2026fanarsadiq,
title = {{Fanar-Sadiq}: A Multi-Agent Architecture for Grounded Islamic QA},
author = {Abbas, Ummar and Ouzzani, Mourad and Eltabakh, Mohamed Y. and Sinan, Omar and Bhatia, Gagan and Mubarak, Hamdy and Hawasly, Majd and Hashim, Mohammed Qusay and Darwish, Kareem and Alam, Firoj},
booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics},
address = {San Diego, California, United States},
publisher = {Association for Computational Linguistics},
year = {2026},
url = {https://arxiv.org/abs/2603.08501},
}
@article{Bhatia_2026,
title={Advances in AI Systems on Islamic Knowledge Capabilities: A Critical Survey},
publisher={Institute of Electrical and Electronics Engineers (IEEE)},
author={Bhatia, Gagan and Mubarak, Hamdy and Hawasly, Majd and Jarrar, Mustafa and Mikros, George and Zaraket, Fadi and Alhirthani, Mahmoud and Al-Khatib, Mutaz and Cochrane, Logan and Darwish, Kareem and Yahiaoui, Rashid and Alam, Firoj},
url={http://dx.doi.org/10.36227/techrxiv.177155997.77147487/v1},
DOI={10.36227/techrxiv.177155997.77147487/v1},
year={2026},
}
@article{ali2026menaspeechbankreferencevoicebank,
title = {{MENASpeechBank}: A Reference Voice Bank with Persona-Conditioned Multi-Turn Conversations for AudioLLMs},
author = {Ali, Zien Sheikh and Bhatti, Hunzalah Hassan and Nandi, Rabindra Nath and Chowdhury, Shammur Absar and Alam, Firoj},
journal = {arXiv preprint arXiv:2602.07036},
year = {2026},
url = {https://arxiv.org/abs/2602.07036},
}
@inproceedings{shahroor2026memelens,
title = {{MemeLens}: Multilingual Multitask VLMs for Memes},
author = {Shahroor, Ali Ezzat and Kmainasi, Mohamed Bayan and Hasnat, Abul and Dimitrov, Dimitar and Da San Martino, Giovanni and Nakov, Preslav and Alam, Firoj},
booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics},
address = {San Diego, California, United States},
publisher = {Association for Computational Linguistics},
year = {2026},
url = {https://arxiv.org/abs/2601.12539},
}
@article{bhatti2026harmonizingarabicaudiospace,
title = {Multi-Task Instruction Tuning via Data Scheduling for Low-Resource Arabic AudioLLMs},
author = {Bhatti, Hunzalah Hassan and Alam, Firoj and Chowdhury, Shammur Absar},
journal = {arXiv preprint arXiv:2601.12494},
year = {2026},
url = {https://arxiv.org/abs/2601.12494},
}
@inproceedings{mousi2026counterfactualhallucination,
title = {Once Correct, Still Wrong: Counterfactual Hallucination in Multilingual Vision-Language Models},
author = {Mousi, Basel and Dalvi, Fahim and Chowdhury, Shammur and Alam, Firoj and Durrani, Nadir},
booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics},
address = {San Diego, California, United States},
publisher = {Association for Computational Linguistics},
year = {2026},
url = {https://arxiv.org/abs/2602.05437},
}
@inproceedings{bhatia2026agenticrag,
title = {From {RAG} to {Agentic RAG} for Faithful Islamic Question Answering},
author = {Bhatia, Gagan and Mubarak, Hamdy and Jarrar, Mustafa and Mikros, George and Zaraket, Fadi and Alhirthani, Mahmoud and Al-Khatib, Mutaz and Cochrane, Logan and Darwish, Kareem and Yahiaoui, Rashid and Alam, Firoj},
booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics},
address = {San Diego, California, United States},
publisher = {Association for Computational Linguistics},
year = {2026},
url = {https://doi.org/10.48550/arXiv.2601.07528},
}
@article{alam2025everydaymmqa,
title={{EverydayMMQA}: A Multilingual and Multimodal Framework for Culturally Grounded Spoken Visual QA},
author= {Alam, Firoj and Shahroor, Ali Ezzat and Hasan, Md. Arid and Ali, Zien Sheikh and Bhatti, Hunzalah Hassan and Kmainasi, Mohamed Bayan and Chowdhury, Shammur Absar and Mousi, Basel and Dalvi, Fahim and Durrani, Nadir and Milic-Frayling, Natasa},
journal={arXiv preprint arXiv:2510.06371},
year={2025}
}
@inproceedings{bhatti2025beyond,
title={{Beyond MCQ}: An Open-Ended Arabic Cultural QA Benchmark with Dialect Variants},
author={Bhatti, Hunzalah Hassan and Alam, Firoj},
booktitle={The 15th edition of the Language Resources and Evaluation Conference (LREC 2026)},
year={2026},
}
@article{abouzied2025combating,
title={Combating Misinformation in the Arab World: Challenges and Opportunities},
author={Abouzied, Azza and Alam, Firoj and Ali, Raian and Papotti, Paolo},
journal={Communications of the ACM},
volume={68},
number={10},
pages={48--53},
year={2025},
publisher={ACM New York, NY, USA}
}
@article{al2025landscape,
title={The Landscape of Arabic Large Language Models},
author={Al-Khalifa, Shahad and Durrani, Nadir and Al-Khalifa, Hend and Alam, Firoj},
journal={Communications of the ACM},
volume={68},
number={10},
pages={54--61},
year={2025},
publisher={ACM New York, NY, USA}
}
@inproceedings{kmainasi-etal-2025-memeintel,
title = "{M}eme{I}ntel: Explainable Detection of Propagandistic and Hateful Memes",
author = "Kmainasi, Mohamed Bayan and
Hasnat, Abul and
Hasan, Md Arid and
Shahroor, Ali Ezzat and
Alam, Firoj",
editor = "Christodoulopoulos, Christos and
Chakraborty, Tanmoy and
Rose, Carolyn and
Peng, Violet",
booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.emnlp-main.1539/",
doi = "10.18653/v1/2025.emnlp-main.1539",
pages = "30251--30267",
ISBN = "979-8-89176-332-6"
}
@inproceedings{bassi-etal-2025-annotating,
title = "Annotating the Annotators: Analysis, Insights and Modelling from an Annotation Campaign on Persuasion Techniques Detection",
author = "Bassi, Davide and
Dimitrov, Dimitar Iliyanov and
D{'}Auria, Bernardo and
Alam, Firoj and
Hasanain, Maram and
Moro, Christian and
Orr{\`u}, Luisa and
Turchi, Gian Piero and
Nakov, Preslav and
Da San Martino, Giovanni",
editor = "Che, Wanxiang and
Nabende, Joyce and
Shutova, Ekaterina and
Pilehvar, Mohammad Taher",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-acl.922/",
doi = "10.18653/v1/2025.findings-acl.922",
pages = "17918--17929",
ISBN = "979-8-89176-256-5"
}
@inproceedings{hasanain-etal-2025-propxplain,
title = "{P}rop{X}plain: Can {LLM}s Enable Explainable Propaganda Detection?",
author = "Hasanain, Maram and
Hasan, Md Arid and
Kmainasi, Mohamed Bayan and
Sartori, Elisa and
Shahroor, Ali Ezzat and
Da San Martino, Giovanni and
Alam, Firoj",
editor = "Christodoulopoulos, Christos and
Chakraborty, Tanmoy and
Rose, Carolyn and
Peng, Violet",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-emnlp.1296/",
doi = "10.18653/v1/2025.findings-emnlp.1296",
pages = "23855--23863",
ISBN = "979-8-89176-335-7"
}
@inproceedings{hasan-etal-2025-nativqa,
title = "{N}ativ{QA}: Multilingual Culturally-Aligned Natural Query for {LLM}s",
author = "Hasan, Md. Arid and
Hasanain, Maram and
Ahmad, Fatema and
Laskar, Sahinur Rahman and
Upadhyay, Sunaya and
Sukhadia, Vrunda N and
Kutlu, Mucahid and
Chowdhury, Shammur Absar and
Alam, Firoj",
editor = "Che, Wanxiang and
Nabende, Joyce and
Shutova, Ekaterina and
Pilehvar, Mohammad Taher",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-acl.770/",
doi = "10.18653/v1/2025.findings-acl.770",
pages = "14886--14909",
ISBN = "979-8-89176-256-5"
}
@inproceedings{hassan-bhatti-etal-2025-cultranai,
title = "{C}ultran{AI} at {P}alm{X} 2025: Data Augmentation for Cultural Knowledge Representation",
author = "Hassan Bhatti, Hunzalah and
Ahmed, Youssef and
Arid Hasan, Md and
Alam, Firoj",
editor = "Darwish, Kareem and
Ali, Ahmed and
Abu Farha, Ibrahim and
Touileb, Samia and
Zitouni, Imed and
Abdelali, Ahmed and
Al-Ghamdi, Sharefah and
Alkhereyf, Sakhar and
Zaghouani, Wajdi and
Khalifa, Salam and
AlKhamissi, Badr and
Almatham, Rawan and
Hamed, Injy and
Alyafeai, Zaid and
Alowisheq, Areeb and
Inoue, Go and
Mrini, Khalil and
Alshammari, Waad",
booktitle = "Proceedings of The Third Arabic Natural Language Processing Conference: Shared Tasks",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.arabicnlp-sharedtasks.111/",
doi = "10.18653/v1/2025.arabicnlp-sharedtasks.111",
pages = "809--817",
ISBN = "979-8-89176-356-2"
}
@inproceedings{rafiul-biswas-etal-2025-marsadlab-palmx,
title = "{M}arsad{L}ab at {P}alm{X} Shared Task: An {LLM} Benchmark for {A}rabic Culture and Islamic Civilization",
author = "Rafiul Biswas, Md. and
Ibrahim, Shimaa and
Attia, Kais and
Alam, Firoj and
Zaghouani, Wajdi",
editor = "Darwish, Kareem and
Ali, Ahmed and
Abu Farha, Ibrahim and
Touileb, Samia and
Zitouni, Imed and
Abdelali, Ahmed and
Al-Ghamdi, Sharefah and
Alkhereyf, Sakhar and
Zaghouani, Wajdi and
Khalifa, Salam and
AlKhamissi, Badr and
Almatham, Rawan and
Hamed, Injy and
Alyafeai, Zaid and
Alowisheq, Areeb and
Inoue, Go and
Mrini, Khalil and
Alshammari, Waad",
booktitle = "Proceedings of The Third Arabic Natural Language Processing Conference: Shared Tasks",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.arabicnlp-sharedtasks.112/",
doi = "10.18653/v1/2025.arabicnlp-sharedtasks.112",
pages = "818--824",
ISBN = "979-8-89176-356-2"
}
@inproceedings{tajrin-etal-2025-aya,
title = "{AYA} at {P}alm{X} 2025: Modeling Cultural and Islamic Knowledge in {LLM}s",
author = "Tajrin, Jannatul and
Ballav Roy, Bir and
Alam, Firoj",
editor = "Darwish, Kareem and
Ali, Ahmed and
Abu Farha, Ibrahim and
Touileb, Samia and
Zitouni, Imed and
Abdelali, Ahmed and
Al-Ghamdi, Sharefah and
Alkhereyf, Sakhar and
Zaghouani, Wajdi and
Khalifa, Salam and
AlKhamissi, Badr and
Almatham, Rawan and
Hamed, Injy and
Alyafeai, Zaid and
Alowisheq, Areeb and
Inoue, Go and
Mrini, Khalil and
Alshammari, Waad",
booktitle = "Proceedings of The Third Arabic Natural Language Processing Conference: Shared Tasks",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.arabicnlp-sharedtasks.114/",
doi = "10.18653/v1/2025.arabicnlp-sharedtasks.114",
pages = "830--836",
ISBN = "979-8-89176-356-2"
}
@inproceedings{rafiul-biswas-etal-2025-marsadlab,
title = "{M}arsad{L}ab at {A}ra{G}en{E}val Shared Task: {LLM}-Based Approaches to {A}rabic Authorship Style Transfer and Identification",
author = "Rafiul Biswas, Md. and
Bessghaier, Mabrouka and
Alam, Firoj and
Zaghouani, Wajdi",
editor = "Darwish, Kareem and
Ali, Ahmed and
Abu Farha, Ibrahim and
Touileb, Samia and
Zitouni, Imed and
Abdelali, Ahmed and
Al-Ghamdi, Sharefah and
Alkhereyf, Sakhar and
Zaghouani, Wajdi and
Khalifa, Salam and
AlKhamissi, Badr and
Almatham, Rawan and
Hamed, Injy and
Alyafeai, Zaid and
Alowisheq, Areeb and
Inoue, Go and
Mrini, Khalil and
Alshammari, Waad",
booktitle = "Proceedings of The Third Arabic Natural Language Processing Conference: Shared Tasks",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.arabicnlp-sharedtasks.15/",
doi = "10.18653/v1/2025.arabicnlp-sharedtasks.15",
pages = "88--93",
ISBN = "979-8-89176-356-2"
}
@inproceedings{zaghouani-etal-2025-mahed,
title = "{MAHED} Shared Task: Multimodal Detection of Hope and Hate Emotions in {A}rabic Content",
author = "Zaghouani, Wajdi and
Biswas, Md. Rafiul and
Bessghaier, Mabrouka and
Ibrahim, Shimaa and
Mikros, George and
Hasnat, Abul and
Alam, Firoj",
editor = "Darwish, Kareem and
Ali, Ahmed and
Abu Farha, Ibrahim and
Touileb, Samia and
Zitouni, Imed and
Abdelali, Ahmed and
Al-Ghamdi, Sharefah and
Alkhereyf, Sakhar and
Zaghouani, Wajdi and
Khalifa, Salam and
AlKhamissi, Badr and
Almatham, Rawan and
Hamed, Injy and
Alyafeai, Zaid and
Alowisheq, Areeb and
Inoue, Go and
Mrini, Khalil and
Alshammari, Waad",
booktitle = "Proceedings of The Third Arabic Natural Language Processing Conference: Shared Tasks",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.arabicnlp-sharedtasks.75/",
doi = "10.18653/v1/2025.arabicnlp-sharedtasks.75",
pages = "560--574",
ISBN = "979-8-89176-356-2"
}
@inproceedings{almatham-etal-2025-balsam,
title = "{BALSAM}: A Platform for Benchmarking {A}rabic Large Language Models",
author = "Almatham, Rawan Nasser and
Darwish, Kareem Mohamed and
Al-Rasheed, Raghad and
Alshammari, Waad Thuwaini and
Alhoshan, Muneera and
Almazrua, Amal and
Al Wazrah, Asma and
Alheraki, Mais and
Alam, Firoj and
Nakov, Preslav and
Alzahrani, Norah A. and
Albilali, Eman and
Habash, Nizar and
El-Sheikh, Abdelrahman Mustafa and
Elmallah, Muhammad and
Mubarak, Hamdy and
Alyafeai, Zaid and
Anwar, Mohamed and
Li, Haonan and
Abdelali, Ahmed and
Altwairesh, Nora and
Hasanain, Maram and
Al-Thubaity, Abdulmohsen and
Shehata, Shady and
Alhafni, Bashar and
Hamed, Injy and
Inoue, Go and
Elmadani, Khalid N. and
Obeid, Ossama and
Haouari, Fatima and
Elsayed, Tamer and
Alghamdi, Emad A. and
Almubarak, Khalid and
Alshahrani, Saied and
Aljareh, Ola and
Alajlan, Safa and
Alshaqarawi, Areej and
Alshihri, Maryam and
Alghurabi, Sultana and
Alzeghayer, Atikah and
Altamimi, Afrah and
Alfaifi, Abdullah and
Alosaimy, Abdulrahman M",
editor = "Darwish, Kareem and
Ali, Ahmed and
Abu Farha, Ibrahim and
Touileb, Samia and
Zitouni, Imed and
Abdelali, Ahmed and
Al-Ghamdi, Sharefah and
Alkhereyf, Sakhar and
Zaghouani, Wajdi and
Khalifa, Salam and
AlKhamissi, Badr and
Almatham, Rawan and
Hamed, Injy and
Alyafeai, Zaid and
Alowisheq, Areeb and
Inoue, Go and
Mrini, Khalil and
Alshammari, Waad",
booktitle = "Proceedings of The Third Arabic Natural Language Processing Conference",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.arabicnlp-main.21/",
doi = "10.18653/v1/2025.arabicnlp-main.21",
pages = "258--277",
ISBN = "979-8-89176-352-4"
}
@inproceedings{alam2025overview,
title={Overview of the CLEF-2025 CheckThat! Lab: Subjectivity, fact-checking, claim normalization, and retrieval},
author={Alam, Firoj and Stru{\ss}, Julia Maria and Chakraborty, Tanmoy and Dietze, Stefan and Hafid, Salim and Korre, Katerina and Muti, Arianna and Nakov, Preslav and Ruggeri, Federico and Schellhammer, Sebastian and others},
booktitle={International Conference of the Cross-Language Evaluation Forum for European Languages},
pages={199--223},
year={2025},
organization={Springer}
}
@inproceedings{alam2025clef,
title={The CLEF-2025 CheckThat! Lab: Subjectivity, Fact-Checking, Claim Normalization, and Retrieval},
author={Alam, Firoj and Stru{\ss}, Julia Maria and Chakraborty, Tanmoy and Dietze, Stefan and Hafid, Salim and Korre, Katerina and Muti, Arianna and Nakov, Preslav and Ruggeri, Federico and Schellhammer, Sebastian and others},
booktitle={European Conference on Information Retrieval},
pages={467--478},
year={2025},
organization={Springer}
}
@inproceedings{Ersoy2025from,
title={From Words to Waves: Analyzing Concept Formation in Speech and Text-Based Foundation Models},
author={ Ersoy, Asim and Mousi, Basel Ahmad and Chowdhury, Shammur Absar and Alam, Firoj and Dalvi, Fahim I and Durrani, Nadir},
booktitle = {{Proc. of the 26th Annual Conference of the International Speech Communication Association (INTERSPEECH)}},
year={2025}
}
@inproceedings{Alam2025SpokenNativQA,
title={SpokenNativQA: Multilingual Everyday Spoken Queries for LLMs},
author={Alam, Firoj and Hasan, Md Arid and Chowdhury, Shammur Absar},
booktitle = {{Proc. of the 26th Annual Conference of the International Speech Communication Association (INTERSPEECH)}},
year={2025}
}
@inproceedings{10.1145/3706598.3713150,
author = {Magdy, Walid and Mubarak, Hamdy and Salminen, Joni},
title = {Who should set the Standards? Analysing Censored Arabic Content on Facebook during the Palestine-Israel Conflict},
year = {2025},
isbn = {9798400713941},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3706598.3713150},
doi = {10.1145/3706598.3713150},
abstract = {Nascent research on human-computer interaction concerns itself with fairness of content moderation systems. Designing globally applicable content moderation systems requires considering historical, cultural, and socio-technical factors. Inspired by this line of work, we investigate Arab users’ perception of Facebook’s moderation practices. We collect a set of 448 deleted Arabic posts, and we ask Arab annotators to evaluate these posts based on (a) Facebook Community Standards (FBCS) and (b) their personal opinion. Each post was judged by 10 annotators to account for subjectivity. Our analysis shows a clear gap between the Arabs’ understanding of the FBCS and how Facebook implements these standards. The study highlights a need for discussion on the moderation guidelines on social media platforms about who decides the moderation guidelines, how these guidelines are interpreted, and how well they represent the views of marginalised user communities.},
booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems},
articleno = {178},
numpages = {16},
keywords = {Censorship, Content Moderation, Free Speech, Facebook, Social Media, Palestine Israel Conflict},
location = {
},
series = {CHI '25}
}
@inproceedings{yu-etal-2024-latent,
title = "Latent Concept-based Explanation of {NLP} Models",
author = "Yu, Xuemin and
Dalvi, Fahim and
Durrani, Nadir and
Nouri, Marzia and
Sajjad, Hassan",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.emnlp-main.692/",
doi = "10.18653/v1/2024.emnlp-main.692",
pages = "12435--12459",
abstract = "Interpreting and understanding the predictions made by deep learning models poses a formidable challenge due to their inherently opaque nature. Many previous efforts aimed at explaining these predictions rely on input features, specifically, the words within NLP models. However, such explanations are often less informative due to the discrete nature of these words and their lack of contextual verbosity. To address this limitation, we introduce the Latent Concept Attribution method (LACOAT), which generates explanations for predictions based on latent concepts. Our foundational intuition is that a word can exhibit multiple facets, contingent upon the context in which it is used. Therefore, given a word in context, the latent space derived from our training process reflects a specific facet of that word. LACOAT functions by mapping the representations of salient input words into the training latent space, allowing it to provide latent context-based explanations of the prediction."
}
@inproceedings{hasanain-etal-2024-large,
title = "Large Language Models for Propaganda Span Annotation",
author = "Hasanain, Maram and
Ahmad, Fatema and
Alam, Firoj",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-emnlp.850/",
doi = "10.18653/v1/2024.findings-emnlp.850",
pages = "14522--14532",
abstract = "The use of propagandistic techniques in online content has increased in recent years aiming to manipulate online audiences. Fine-grained propaganda detection and extraction of textual spans where propaganda techniques are used, are essential for more informed content consumption. Automatic systems targeting the task over lower resourced languages are limited, usually obstructed by lack of large scale training datasets. Our study investigates whether Large Language Models (LLMs), such as GPT-4, can effectively extract propagandistic spans. We further study the potential of employing the model to collect more cost-effective annotations. Finally, we examine the effectiveness of labels provided by GPT-4 in training smaller language models for the task. The experiments are performed over a large-scale in-house manually annotated dataset. The results suggest that providing more annotation context to GPT-4 within prompts improves its performance compared to human annotators. Moreover, when serving as an expert annotator (consolidator), the model provides labels that have higher agreement with expert annotators, and lead to specialized models that achieve state-of-the-art over an unseen Arabic testing set. Finally, our work is the first to show the potential of utilizing LLMs to develop annotated datasets for propagandistic spans detection task prompting it with annotations from human annotators with limited expertise. All scripts and annotations will be shared with the community."
}
@inproceedings{abdaljalil-mubarak-2024-wikidata,
title = "{W}ikidata as a Source of Demographic Information",
author = "Abdaljalil, Samir and
Mubarak, Hamdy",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farha, Ibrahim and
Abdelali, Ahmed and
Touileb, Samia and
Hamed, Injy and
Onaizan, Yaser and
Alhafni, Bashar and
Antoun, Wissam and
Khalifa, Salam and
Haddad, Hatem and
Zitouni, Imed and
AlKhamissi, Badr and
Almatham, Rawan and
Mrini, Khalil",
booktitle = "Proceedings of the Second Arabic Natural Language Processing Conference",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.arabicnlp-1.1/",
doi = "10.18653/v1/2024.arabicnlp-1.1",
pages = "1--10",
abstract = "Names carry important information about our identities and demographics such as gender, nationality, ethnicity, etc. We investigate the use of individual{'}s name, in both Arabic and English, to predict important attributes, namely country, region, gender, and language. We extract data from Wikidata, and normalize it, to build a comprehensive dataset consisting of more than 1 million entities and their normalized attributes. We experiment with a Linear SVM approach, as well as two Transformers approaches consisting of BERT model fine-tuning and Transformers pipeline. Our results indicate that we can predict the gender, language and region using the name only with a confidence over 0.65. The country attribute can be predicted with less accuracy. The Linear SVM approach outperforms the other approaches for all the attributes. The best performing approach was also evaluated on another dataset that consists of 1,500 names from 15 countries (covering different regions) extracted from Twitter, and yields similar results."
}
@inproceedings{fadeeva-etal-2024-fact,
title = "Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification",
author = "Fadeeva, Ekaterina and
Rubashevskii, Aleksandr and
Shelmanov, Artem and
Petrakov, Sergey and
Li, Haonan and
Mubarak, Hamdy and
Tsymbalov, Evgenii and
Kuzmin, Gleb and
Panchenko, Alexander and
Baldwin, Timothy and
Nakov, Preslav and
Panov, Maxim",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2024",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-acl.558/",
doi = "10.18653/v1/2024.findings-acl.558",
pages = "9367--9385",
abstract = "Large language models (LLMs) are notorious for hallucinating, i.e., producing erroneous claims in their output. Such hallucinations can be dangerous, as occasional factual inaccuracies in the generated text might be obscured by the rest of the output being generally factually correct, making it extremely hard for the users to spot them. Current services that leverage LLMs usually do not provide any means for detecting unreliable generations. Here, we aim to bridge this gap. In particular, we propose a novel fact-checking and hallucination detection pipeline based on token-level uncertainty quantification. Uncertainty scores leverage information encapsulated in the output of a neural network or its layers to detect unreliable predictions, and we show that they can be used to fact-check the atomic claims in the LLM output. Moreover, we present a novel token-level uncertainty quantification method that removes the impact of uncertainty about what claim to generate on the current step and what surface form to use. Our method Claim Conditioned Probability (CCP) measures only the uncertainty of a particular claim value expressed by the model. Experiments on the task of biography generation demonstrate strong improvements for CCP compared to the baselines for seven different LLMs and four languages. Human evaluation reveals that the fact-checking pipeline based on uncertainty quantification is competitive with a fact-checking tool that leverages external knowledge."
}
@inproceedings{zaghouani-etal-2024-hateful,
title = "So Hateful! Building a Multi-Label Hate Speech Annotated {A}rabic Dataset",
author = "Zaghouani, Wajdi and
Mubarak, Hamdy and
Biswas, Md. Rafiul",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.1308/",
pages = "15044--15055",
abstract = "Social media enables widespread propagation of hate speech targeting groups based on ethnicity, religion, or other characteristics. With manual content moderation being infeasible given the volume, automatic hate speech detection is essential. This paper analyzes 70,000 Arabic tweets, from which 15,965 tweets were selected and annotated, to identify hate speech patterns and train classification models. Annotators labeled the Arabic tweets for offensive content, hate speech, emotion intensity and type, effect on readers, humor, factuality, and spam. Key findings reveal 15{\%} of tweets contain offensive language while 6{\%} have hate speech, mostly targeted towards groups with common ideological or political affiliations. Annotations capture diverse emotions, and sarcasm is more prevalent than humor. Additionally, 10{\%} of tweets provide verifiable factual claims, and 7{\%} are deemed important. For hate speech detection, deep learning models like AraBERT outperform classical machine learning approaches. By providing insights into hate speech characteristics, this work enables improved content moderation and reduced exposure to online hate. The annotated dataset advances Arabic natural language processing research and resources."
}
@inproceedings{mubarak-etal-2024-halwasa,
title = "Halwasa: Quantify and Analyze Hallucinations in Large Language Models: {A}rabic as a Case Study",
author = "Mubarak, Hamdy and
Al-Khalifa, Hend and
Alkhalefah, Khaloud Suliman",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.705/",
pages = "8008--8015",
abstract = "Large Language Models (LLMs) have shown superb abilities to generate texts that are indistinguishable from human-generated texts in many cases. However, sometimes they generate false, incorrect, or misleading content, which is often described as {\textquotedblleft}hallucinations{\textquotedblright}. Quantifying and analyzing hallucination in LLMs can increase their reliability and usage. While hallucination is being actively studied for English and other languages, and different benchmarking datsets have been created, this area is not studied at all for Arabic. In our paper, we create the first Arabic dataset that contains 10K of generated sentences by LLMs and annotate it for factuality and correctness. We provide detailed analysis of the dataset to analyze factual and linguistic errors. We found that 25{\%} of the generated sentences are factually incorrect. We share the dataset with the research community."
}
>>>>>>> upstream/master
@inproceedings{ThatiAR2025,
title = {{ThatiAR}: Subjectivity Detection in Arabic News Sentences},
author = {Reem Suwaileh and Maram Hasanain and Fatema Hubail and Wajdi Zaghouani and Firoj Alam},
booktitle = {Proceedings of the International AAAI Conference on Web and Social Media (ICWSM 2025)},
year = {2025},
address = {Copenhagen, Denmark},
month = jun,
}
@inproceedings{kmainasi-etal-2025-llamalens,
title = "{L}lama{L}ens: Specialized Multilingual {LLM} for Analyzing News and Social Media Content",
author = "Kmainasi, Mohamed Bayan and
Shahroor, Ali Ezzat and
Hasanain, Maram and
Laskar, Sahinur Rahman and
Hassan, Naeemul and
Alam, Firoj",
editor = "Chiruzzo, Luis and
Ritter, Alan and
Wang, Lu",
booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-naacl.313/",
pages = "5627--5649",
ISBN = "979-8-89176-195-7",
}
@inproceedings{basher-etal-2025-bntts,
title = "{B}n{TTS}: Few-Shot Speaker Adaptation in Low-Resource Setting",
author = "Basher, Mohammad Jahid Ibna and
Kowsher, Md and
Islam, Md Saiful and
Nandi, Rabindra Nath and
Prottasha, Nusrat Jahan and
Menon, Mehadi Hasan and
Muntasir, Tareq Al and
Chowdhury, Shammur Absar and
Alam, Firoj and
Yousefi, Niloofar and
Garibay, Ozlem",
editor = "Chiruzzo, Luis and
Ritter, Alan and
Wang, Lu",
booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-naacl.279/",
pages = "4956--4968",
ISBN = "979-8-89176-195-7",
}
@InProceedings{10.1007/978-3-031-88720-8_68,
author="Alam, Firoj
and Stru{\ss}, Julia Maria
and Chakraborty, Tanmoy
and Dietze, Stefan
and Hafid, Salim
and Korre, Katerina
and Muti, Arianna
and Nakov, Preslav
and Ruggeri, Federico
and Schellhammer, Sebastian
and Setty, Vinay
and Sundriyal, Megha
and Todorov, Konstantin
and V., Venktesh",
editor="Hauff, Claudia
and Macdonald, Craig
and Jannach, Dietmar
and Kazai, Gabriella
and Nardini, Franco Maria
and Pinelli, Fabio
and Silvestri, Fabrizio
and Tonellotto, Nicola",
title="The CLEF-2025 CheckThat! Lab: Subjectivity, Fact-Checking, Claim Normalization, and Retrieval",
booktitle="Advances in Information Retrieval",
year="2025",
publisher="Springer Nature Switzerland",
address="Cham",
pages="467--478",
isbn="978-3-031-88720-8",
}
@inproceedings{mousi-etal-2025-aradice,
title = "{A}ra{D}i{CE}: Benchmarks for Dialectal and Cultural Capabilities in {LLM}s",
author = "Mousi, Basel and
Durrani, Nadir and
Ahmad, Fatema and
Hasan, Md. Arid and
Hasanain, Maram and
Kabbani, Tameem and
Dalvi, Fahim and
Chowdhury, Shammur Absar and
Alam, Firoj",
editor = "Rambow, Owen and
Wanner, Leo and
Apidianaki, Marianna and
Al-Khalifa, Hend and
Eugenio, Barbara Di and
Schockaert, Steven",
booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.coling-main.283/",
pages = "4186--4218",
}
@inproceedings{chowdhury-etal-2025-genai,
title = "{G}en{AI} Content Detection Task 2: {AI} vs. Human {--} Academic Essay Authenticity Challenge",
author = "Chowdhury, Shammur Absar and
Almerekhi, Hind and
Kutlu, Mucahid and
Kele{\c{s}}, Kaan Efe and
Ahmad, Fatema and
Mohiuddin, Tasnim and
Mikros, George and
Alam, Firoj",
editor = "Alam, Firoj and
Nakov, Preslav and
Habash, Nizar and
Gurevych, Iryna and
Chowdhury, Shammur and
Shelmanov, Artem and
Wang, Yuxia and
Artemova, Ekaterina and
Kutlu, Mucahid and
Mikros, George",
booktitle = "Proceedings of the 1stWorkshop on GenAI Content Detection (GenAIDetect)",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "International Conference on Computational Linguistics",
url = "https://aclanthology.org/2025.genaidetect-1.37/",
pages = "323--333",
}
@inproceedings{dugan-etal-2025-genai,
title = "{G}en{AI} Content Detection Task 3: Cross-Domain Machine Generated Text Detection Challenge",
author = "Dugan, Liam and
Zhu, Andrew and
Alam, Firoj and
Nakov, Preslav and
Apidianaki, Marianna and
Callison-Burch, Chris",
editor = "Alam, Firoj and
Nakov, Preslav and
Habash, Nizar and
Gurevych, Iryna and
Chowdhury, Shammur and
Shelmanov, Artem and
Wang, Yuxia and
Artemova, Ekaterina and
Kutlu, Mucahid and
Mikros, George",
booktitle = "Proceedings of the 1stWorkshop on GenAI Content Detection (GenAIDetect)",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "International Conference on Computational Linguistics",
url = "https://aclanthology.org/2025.genaidetect-1.45/",
pages = "377--388",
}
@proceedings{genaidetect-ws-2025-1,
title = "Proceedings of the 1stWorkshop on GenAI Content Detection (GenAIDetect)",
editor = "Alam, Firoj and
Nakov, Preslav and
Habash, Nizar and
Gurevych, Iryna and
Chowdhury, Shammur and
Shelmanov, Artem and
Wang, Yuxia and
Artemova, Ekaterina and
Kutlu, Mucahid and
Mikros, George",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "International Conference on Computational Linguistics",
url = "https://aclanthology.org/2025.genaidetect-1.0/"
}
@inproceedings{vrunda2024,
title={Children’s Speech Recognition through Discrete Token Enhancement},
author={Sukhadia, Vrunda N. and Chowdhury, Shammur Absar },
booktitle = {{Proc. of the 25th Annual Conference of the International Speech Communication Association (INTERSPEECH)}},
year={2024}
}
@inproceedings{ElKheir2024Beyond,
title={Beyond Orthography: Automatic Recovery of Short Vowels and Dialectal Sounds in Arabic},
author={Yassine El Kheir and Hamdy Mubarak and Ahmed Ali and Shammur Absar Chowdhury},
booktitle={Proc. of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL)},
year={2024}
}
@inproceedings{el2024l1,
title={L1-aware multilingual mispronunciation detection framework},
author={El Kheir, Yassine and Chowdhury, Shammur Absar and Ali, Ahmed},
booktitle={Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={12752--12756},
year={2024},
organization={IEEE}
}
@inproceedings{el2024speech,
title={Speech representation analysis based on inter-and intra-model similarities},
author={El Kheir, Yassine and Ali, Ahmed and Chowdhury, Shammur Absar},
booktitle={2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)},
pages={848--852},
year={2024},
organization={IEEE}
}
@inproceedings{hussein2024speech,
title={Speech collage: code-switched audio generation by collaging monolingual corpora},
author={Hussein, Amir and Zeinali, Dorsa and Klejch, Ond{\v{r}}ej and Wiesner, Matthew and Yan, Brian and Chowdhury, Shammur and Ali, Ahmed and Watanabe, Shinji and Khudanpur, Sanjeev},
booktitle={Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={12006--12010},
year={2024},
organization={IEEE}
}
@inproceedings{kheir2023automatic,
title={Automatic Pronunciation Assessment-A Review},
author={Kheir, Yassine and Ali, Ahmed and Chowdhury, Shammur},
booktitle={Proc. of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
pages={8304--8324},
year={2023}
}
@inproceedings{speechBlender2023,
author = {Yassine El Kheir and Shammur Absar Chowdhury and Ahmed Ali},
title = {Speechblender: Speech augmentation framework for mispronunciation data generation},
booktitle = {Proc. of the Speech and Language Technology in Education (SLaTE)},
year = {2023}
}
@inproceedings{multiview2023,
author = {Yassine El Kheir and Shammur Absar Chowdhury and Ahmed Ali},
title = {Multi-View Multi-Task Representation Learning for Mispronunciation Detection},
booktitle = {Proc. of the Speech and Language Technology in Education (SLaTE)},
year = {2023}
}
@article{chowdhury2023end,
title={What do end-to-end speech models learn about speaker, language and channel information? a layer-wise and neuron-level analysis},
author={Chowdhury, Shammur Absar and Durrani, Nadir and Ali, Ahmed},
journal={Computer Speech \& Language},
volume={83},
pages={101539},
year={2023},
publisher={Elsevier}
}
@inproceedings{hamed2023benchmarking,
title={Benchmarking Evaluation Metrics for Code-Switching Automatic Speech Recognition},
author={Hamed, Injy and Hussein, Amir and Chellah, Oumnia and Chowdhury, Shammur and Mubarak, Hamdy and Sitaram, Sunayana and Habash, Nizar and Ali, Ahmed},
booktitle={Proc. of the 2022 IEEE Spoken Language Technology Workshop (SLT)},
pages={999--1005},
year={2022},
organization={IEEE}
}
@inproceedings{hussein2023textual,
title={Textual Data Augmentation for Arabic-English Code-Switching Speech Recognition},
author={Hussein, Amir and Chowdhury, Shammur Absar and Abdelali, Ahmed and Dehak, Najim and Ali, Ahmed and Khudanpur, Sanjeev},
booktitle={Proc. of the 2022 IEEE Spoken Language Technology Workshop (SLT)},
pages={777--784},
year={2022},
organization={IEEE}
}
@inproceedings{chowdhury2023multilingual,
title={MULTILINGUAL WORD ERROR RATE ESTIMATION: E-WER3},
author={Chowdhury, Shammur Absar and Ali, Ahmed},
booktitle={ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year={2023}
}
@inproceedings{kheir2023qvoice,
title={QVoice: Arabic Speech Pronunciation Learning Application},
author={Kheir, Yassine El and Khnaisser, Fouad and Chowdhury, Shammur Absar and Mubarak, Hamdy and Afzal, Shazia and Ali, Ahmed},
booktitle={INTERSPEECH},
year={2023}
}
@inproceedings{elshahawy2023myvoice,
title={MyVoice: Arabic Speech Resource Collaboration Platform},
author={Elshahawy, Yousseif and Kheir, Yassine El and Chowdhury, Shammur Absar and Ali, Ahmed},
booktitle={INTERSPEECH},
year={2023}
}
@inproceedings{hamed2022benchmarking,
title={Benchmarking Evaluation Metrics for Code-Switching Automatic Speech Recognition},
author={Hamed, Injy and Hussein, Amir and Chellah, Oumnia and Chowdhury, Shammur and Mubarak, Hamdy and Sitaram, Sunayana and Habash, Nizar and Ali, Ahmed},
booktitle={2022 IEEE Spoken Language Technology Workshop (SLT)},
year={2022}
}
@inproceedings{zamparelli2022semeval,
title={SemEval-2022 Task 3: PreTENS-Evaluating Neural Networks on Presuppositional Semantic Knowledge},
author={Zamparelli, Roberto and Chowdhury, Shammur and Brunato, Dominique and Chesi, Cristiano and Dell’Orletta, Felice and Hasan, Md Arid and Venturi, Giulia},
booktitle={Proc. of the 16th International Workshop on Semantic Evaluation (SemEval-2022)},
pages={228--238},
year={2022}
}
@inproceedings{bayerl2022can,
title={What can Speech and Language Tell us About the Working Alliance in Psychotherapy},
author={Bayerl, Sebastian P and Roccabruna, Gabriel and Chowdhury, Shammur Absar and Ciulli, Tommaso and Danieli, Morena and Riedhammer, Korbinian and Riccardi, Giuseppe},
booktitle = {{{{Proc. of the 23rd Annual Conference of the International Speech Communication Association (INTERSPEECH)}}}},
year={2022}
}
@article{mubarak2022emojis,
title={Emojis as anchors to detect arabic offensive language and hate speech},