Benchmarking Large Language Models for Persian: A Preliminary Study Focusing on ChatGPT (2024.lrec-main)
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Amirhossein Abaskohi, Sara Baruni, Mostafa Masoudi, Nesa Abbasi, Mohammad Hadi Babalou, Ali Edalat, Sepehr Kamahi, Samin Mahdizadeh Sani, Nikoo Naghavian, Danial Namazifard, Pouya Sadeghi, Yadollah Yaghoobzadeh
| Challenge: | a new study examines the efficacy of large language models (LLMs) for Persian . ChatGPT and LLMs have shown remarkable performance in English, but their efficiency for low-resource languages remains an open question. |
| Approach: | They present a benchmarking study of large language models (LLMs) for Persian . they focus on GPT-3.5-turbo, but also GPT-4 and OpenChat-3.5 . |
| Outcome: | The proposed model performs better in Persian than other low-resource languages . the study is the first comprehensive benchmarking of large language models . |
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