Exploring Robustness of Multilingual LLMs on Real-World Noisy Data

Amirhossein Aliakbarzadeh, Lucie Flek, Akbar Karimi

Large Language Models (LLMs) are trained on Web data that might contain spelling errors made by humans. But do they become robust to similar real-world noise? In this paper, we inv…