首页|New Findings from Tianjin University Update Understanding of Machine Translation (Feds-icl: Enhancing Translation Ability and Efficiency of Large Language Model By Optimizing Demonstration Selection)
New Findings from Tianjin University Update Understanding of Machine Translation (Feds-icl: Enhancing Translation Ability and Efficiency of Large Language Model By Optimizing Demonstration Selection)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Translation h ave been presented. According to newsoriginating from Tianjin, People’s Republi c of China, by NewsRx correspondents, research stated, “Largelanguage models (L LMs) that exhibit a remarkable ability by in-context learning (ICL) with bilingu aldemonstrations have been recognized as a potential solution for machine trans lation. However, the processof selecting these demonstrations from vast datasto res is notoriously time-consuming and inefficient.”Financial supporters for this research include National Natural Science Foundati on of China YouthFoud, Key Research and Development Program of Yunnan Province.
TianjinPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningMachine TranslationTianjin Univers ity
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