Papers with CAMEL-Bench
CAMEL-Bench: A Comprehensive Arabic LMM Benchmark (2025.findings-naacl)
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Sara Ghaboura, Ahmed Heakl, Omkar Thawakar, Ali Husain Salem Abdulla Alharthi, Ines Riahi, Abduljalil Radman, Jorma Laaksonen, Fahad Shahbaz Khan, Salman Khan, Rao Muhammad Anwer
| Challenge: | Recent years have witnessed a significant interest in developing large multimodal models capable of performing various visual reasoning and understanding tasks. |
| Approach: | They propose to use Arabic as a language to evaluate large multi-modal models capable of performing visual reasoning and understanding tasks. |
| Outcome: | The proposed benchmark comprises eight diverse domains and 38 sub-domains to represent a large population of over 400 million speakers. |