Robotics & Machine Learning Daily News2024,Issue(Sep.10) :58-58.

Beijing Normal University-Hong Kong Baptist University United International Coll ege Reports Findings in Artificial Intelligence (Enhancing educational Q& A systems using a Chaotic Fuzzy Logic-Augmented large language model)

Robotics & Machine Learning Daily News2024,Issue(Sep.10) :58-58.

Beijing Normal University-Hong Kong Baptist University United International Coll ege Reports Findings in Artificial Intelligence (Enhancing educational Q& A systems using a Chaotic Fuzzy Logic-Augmented large language model)

扫码查看

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Machine Learning-Artificial Int elligence is the subject of a report. According to news reporting originating in Zhuhai, People's Republic of China, by NewsRx journalists, research stated, "On line question-and-answer (Q&A) platforms are frequently replete wit h extensive human resource support. This study proposes a novel methodology of a customized large language model (LLM) called Chaotic LLM-based Educational Q& A System (CHAQS) to navigate the complexities associated with intelligent Q& A systems for the educational sector." The news reporters obtained a quote from the research from Beijing Normal Univer sity-Hong Kong Baptist University United International College, "It uses an expa nsive dataset comprising over 383,000 educational data pairs, an intricate fine- tuning process encompassing p-tuning v2, low-rank adaptation (LRA), and strategi es for parameter freezing at an open-source large language model ChatGLM as a ba seline model. In addition, Fuzzy Logic is implemented to regulate parameters and the system's adaptability with the Lee Oscillator to refine the model's respons e variability and precision. Experiment results showed a 5.12% imp rovement in precision score, an 11% increase in recall metric, and an 8% improvement in the F1 score as compared to other models."

Key words

Zhuhai/People's Republic of China/Asia/Artificial Intelligence/Fuzzy Logic/Machine Learning

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文