electronic dictionary that can

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He has a very famous metaphor: if aliens came to Earth, they would be able to understand and read all the languages ​​on Earth. Because in their view, every language on Earth follows the same grammar, but everyone speaks different "dialects". If htT can switch between multiple languages ​​​​with ease, has it cracked the mystery of the world's universal grammar? Low-resource languages ​​are still underrepresented in large language models. Although large language models have the potential to be transformative, the reality is that large language models mainly cater to English and a few other high-resource languages.



A close examination of the training corpora iran telephone number used by models such as T-T found that there is a clear imbalance between the languages. English dominates. The training corpus of T-T is overwhelmingly English, accounting for . . htT is based on -. Subsequent models such as . continue this trend. Limited representation of languages ​​in the T-corpus: only two languages ​​make up more than 50% of the T-corpus: French and German. Other languages ​​that fall into the 50% range include Spanish, Italian, Portuguese, Dutch, Russian, Romanian, Polish, Finnish, Danish, Swedish, Japanese, and Norwegian.



It is worth noting that languages ​​like Chinese and Hindi, which have more than 100 million speakers combined, do not even make the corpus. Training data concentration: there is a clear head effect for the top languages ​​in the T-training corpus: together they make up 50%. Limited word coverage: only 10 languages ​​have more than 10 million words in the T-training corpus, of which 1 is Khmer. Although Khmer is spoken by 10 million people in Cambodia, it only has 10 million words in the T-training corpus. htT's preference for English and selected high-resource languages ​​is not intentional by htT's parent company; because most of the corpus comes from the Internet, and the Internet reflects the wealth, openness, and activity of a country and language.