Do large-language models contain english condition? Testing and Improving Many LLMS Nature
Great Models of Major Language (LLMS) are more preoccupied in English as the main language, as well as the number of languages that often show strong Ngcing-Centric research. It is like speakers who have not produced negative speeches when learning the second language, the llms often produces non-natural results in non-natural language, indicating the English patterns – Termir. Despite the importance of the matter, the natural environment of many LLM languages have received limited attention. In this paper, we face the expense that imports the automatic corpus metrics to check the Lexical and Syntactic environmental llM outgoing of many languages. We use our new metrics, exploring the car llms are considered chased in French and Chinese, expressing the tendency to the English. In order to reduce the problem, suggest a simple and effective way to measure the LLM site in the target language and domain language, achieving natural environmental development without compromising the functioning of the standard benchmark. Our work highlights the importance of developing many metrics, services and new welsposents of many llms.
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‡ Work is partly done during Apple test
