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pro vyhledávání: '"Toossi, Hasti"'
In the pursuit of supporting more languages around the world, tools that characterize properties of languages play a key role in expanding the existing multilingual NLP research. In this study, we focus on a widely used typological knowledge base, UR
Externí odkaz:
http://arxiv.org/abs/2405.11125
Autor:
Khiu, Eric, Toossi, Hasti, Anugraha, David, Liu, Jinyu, Li, Jiaxu, Flores, Juan Armando Parra, Roman, Leandro Acros, Doğruöz, A. Seza, Lee, En-Shiun Annie
Fine-tuning and testing a multilingual large language model is expensive and challenging for low-resource languages (LRLs). While previous studies have predicted the performance of natural language processing (NLP) tasks using machine learning method
Externí odkaz:
http://arxiv.org/abs/2402.02633