🧑‍🔬 Omkar Thawakar

🏛️ Affiliations

🎓Mohamed bin Zayed University of Artificial IntelligenceAbu Dhabi · United Arab Emirates2022–2026 · 35 paperscurrent🎓Aalto UniversityEspoo · Finland2024–2026 · 2 paperscurrent

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. CAMEL-Bench: A Comprehensive Arabic LMM Benchmark (2025 · 22 citations)
   Most benchmarks for large multimodal models (LMMs) are built around English. This leaves Arabic, with more than 400 million speakers, without a broad way to test models. CAMEL-Bench fills that gap. It is an Arabic evaluation suite covering eight domains and 38 sub-domains:
2. Fann or Flop: A Multigenre, Multiera Benchmark for Arabic Poetry Understanding in LLMs (2025 · 16 citations)
   Large language models handle Arabic well on mainstream benchmarks, but it is unclear whether they grasp Classical Arabic as found in poetry.
3. Arabic Mini-ClimateGPT : A Climate Change and Sustainability Tailored Arabic LLM (2023 · 14 citations)
   Arabic has hundreds of millions of speakers, yet open conversational assistants that can discuss climate change and sustainability in Arabic barely exist.
4. ARB: A Comprehensive Arabic Multimodal Reasoning Benchmark (2026 · 3 citations)
   Benchmarks that check how multimodal models reason step by step, and not only whether the final answer is right, exist almost entirely in English.

All works

5 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. CAMEL-Bench: A Comprehensive Arabic LMM BenchmarkFindings of the Association for Computational LinguisticsSara Ghaboura, Ahmed Heakl, Omkar Thawakar, et al.2025 · 22 citations
2. Fann or Flop: A Multigenre, Multiera Benchmark for Arabic Poetry Understanding in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Wafa Al Ghallabi, Ritesh Thawkar, Sara Ghaboura, et al.2025 · 16 citations
3. Arabic Mini-ClimateGPT : A Climate Change and Sustainability Tailored Arabic LLMFindings of the Association for Computational LinguisticsSahal Shaji Mullappilly, Abdelrahman Shaker, Omkar Thawakar, et al.2023 · 14 citations
4. ARB: A Comprehensive Arabic Multimodal Reasoning BenchmarkLanguage Resources and Evaluation Conference (LREC)Sara Ghaboura, Shubham Patle, Ketan More, et al.2026 · 3 citations
5. DuwatBench: Bridging Language and Visual Heritage through an Arabic Calligraphy Benchmark for Multimodal Understanding ↗Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetShubham Patle et al.2026

🤝 Co-authors here

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

• Rao Muhammad Anwer ×4
• Salman Khan ×4
• Hisham Cholakkal ×3
• Sara Ghaboura ×3
• Jorma Laaksonen ×2
• Ketan Pravin More ×2
• Ahmed Heakl
• Fahad Khan
• Fahad Shahbaz Khan
• Sahal Shaji Mullappilly

Venues

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

• Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2025, Findings of the Association for Computational Linguistics 2023
• Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2025
• Language Resources and Evaluation Conference (LREC): LREC 2026
• Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)

🔗 Cited by

Papers of our library cite their works 41 times (of the 149,439 papers whose bibliographies we read); 26 citing papers with a page here →.

Updated 31 October 2026

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