Robotics & Machine Learning Daily News2024,Issue(Sep.3) :47-48.

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)

Robotics & Machine Learning Daily News2024,Issue(Sep.3) :47-48.

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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Abstract

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.

Key words

Tianjin/People’s Republic of China/Asia/Emerging Technologies/Machine Learning/Machine Translation/Tianjin Univers ity

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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