Evaluating Robustness of Large Language Models Against Multilingual Typographical Errors
arXiv:2510.09536v2 Announce Type: replace
Abstract: Large language models (LLMs) are increasingly deployed in multilingual, real-world applications with user inputs — naturally introducing \emph{typographical errors} (typos). Yet most benchmarks assu…