🧑‍🔬 Gagan Bhatia

🏛️ Affiliations

🎓University of AberdeenAberdeen · United Kingdom2024–2026 · 7 paperscurrent🎓Hamad bin Khalifa UniversityDoha · Qatar2026 · 4 paperscurrent🎓University of Technology NurembergNuremberg · Germany2026 · 1 papercurrent🎓University of British ColumbiaVancouver · Canada2023–2025 · 9 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Peacock: A Family of Arabic Multimodal Large Language Models and Benchmarks (2024 · 28 citations)
   Multimodal LLMs that reason over images work well mainly in English, because other languages lack good image–text resources.
2. Dallah: A Dialect-Aware Multimodal Large Language Model for Arabic (2024 · 25 citations)
   Multimodal LLMs that can discuss images are mostly built for English. Arabic has few image-text resources, and Arabic's regional dialects have almost none. Dallah addresses this gap. It joins the LLaVA framework with AraLLaMA, a LLaMA-2-based model that handles both Arabic and English.
3. Qalam: A Multimodal LLM for Arabic Optical Character and Handwriting Recognition (2024 · 20 citations)
   Arabic text is hard for OCR and handwriting recognition (HWR). The script is cursive, letters change shape with position, and diacritics, dots, ligatures and overlaps all have to be read. Fonts and personal hands vary widely, and annotated data is limited. The authors present Qalam, a vision encoder-decoder…
4. Swan and ArabicMTEB: Dialect-Aware, Arabic-Centric, Cross-Lingual, and Cross-Cultural Embedding Models and Benchmarks (2025 · 13 citations)
   Most text embedding models are built mainly for English and Chinese. They handle Arabic poorly because the language combines rich morphology, many dialects, and culture-specific content. The authors address this with Swan, a pair of Arabic-focused embedding models. Swan-Small is built on ARBERTv2, and Swan-Large is…
5. From RAG to Agentic RAG for Faithful Islamic Question Answering (2026 · 8 citations)
   LLMs are increasingly used to answer Islamic questions, where an unsupported answer can have real religious consequences.

All works

6 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

1. Beyond English: Evaluating LLMs for Arabic Grammatical Error Correction ↗Proceedings of ArabicNLP 2023 · no summary yetSang Kwon et al.2023 · 39 citations
2. Peacock: A Family of Arabic Multimodal Large Language Models and BenchmarksAnnual Meeting of the Association for Computational Linguistics (ACL)Fakhraddin Alwajih, El Moatez Billah Nagoudi, Gagan Bhatia, et al.2024 · 28 citations
3. Dallah: A Dialect-Aware Multimodal Large Language Model for ArabicArabic Natural Language Processing Conference (ArabicNLP)Fakhraddin Alwajih, Gagan Bhatia, Muhammad Abdul-Mageed2024 · 25 citations
4. Qalam: A Multimodal LLM for Arabic Optical Character and Handwriting RecognitionArabic Natural Language Processing Conference (ArabicNLP)Gagan Bhatia, El Moatez Billah Nagoudi, Fakhraddin Alwajih, et al.2024 · 20 citations
5. Swan and ArabicMTEB: Dialect-Aware, Arabic-Centric, Cross-Lingual, and Cross-Cultural Embedding Models and BenchmarksFindings of the Association for Computational LinguisticsGagan Bhatia, El Moatez Billah Nagoudi, Abdellah El Mekki, et al.2025 · 13 citations
6. From RAG to Agentic RAG for Faithful Islamic Question AnsweringFindings of the Association for Computational LinguisticsGagan Bhatia, Hamdy Mubarak, Mustafa Jarrar, et al.2026 · 8 citations

🤝 Co-authors here

12 co-authors with a page, the most papers together first.

• Fakhraddin Alwajih ×4
• Muhammad Abdul-Mageed ×4
• El Moatez Billah Nagoudi ×3
• Abdellah El Mekki
• Abdelrahman Mohamed
• Fadi Zaraket
• Firoj Alam
• George Mikros
• Hamdy Mubarak
• Kareem Darwish
• Mustafa Jarrar
• Mutaz al-Khatib

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Arabic Natural Language Processing Conference (ArabicNLP) ×2: ArabicNLP 2024 ×2
• Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2026, Findings of the Association for Computational Linguistics 2025
• Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2024
• Proceedings of ArabicNLP 2023

🔗 Cited by

Papers of our library cite their works 82 times (of the 149,439 papers whose bibliographies we read); 57 citing papers with a page here →.

Updated 30 October 2026

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