Papers with T5-style models
Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Processing (2022.emnlp-main)
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Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, Ahmad Rashid, Khalil Bibi, Mehdi Rezagholizadeh, Chao Xing, Yasheng Wang, Xinyu Duan, Zhefeng Wang, Baoxing Huai, Xin Jiang, Qun Liu, Phillippe Langlais
| Challenge: | Existing pre-trained language models are not well-explored and are not reproducible in the literature. |
| Approach: | They propose to improve existing Arabic language pre-trained language models using a more methodical approach. |
| Outcome: | The proposed models outperform existing models on ALUE, a leaderboard-powered benchmark for Arabic NLU and NLG tasks. |
AfroBench: How Good are Large Language Models on African Languages? (2025.findings-acl)
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Jessica Ojo, Odunayo Ogundepo, Akintunde Oladipo, Kelechi Ogueji, Jimmy Lin, Pontus Stenetorp, David Ifeoluwa Adelani
| Challenge: | Large-scale multilingual evaluations often include only a handful of African languages due to the scarcity of high-quality data and the limited discoverability of existing datasets. |
| Approach: | They propose a multi-task benchmark to evaluate the performance of LLMs across 64 African languages, 15 tasks and 22 datasets. |
| Outcome: | The proposed benchmark compares LLMs across 64 African languages, 15 tasks and 22 datasets. |