Large Language Model Application Series Salon | The Past and Present of Large Language Models: Exploring the Role of Artificial Intelligence Technology in Language Research

发布时间:2025-12-15浏览次数:10来源:语言科学研究院

Speaker

Li Yan

Time: December 17, 13:30
Venue: Room 5103, Teaching Building No. 5, Songjiang Campus


What is the past and present of large language model technology?
How can artificial intelligence technology assist language research?
Where lies the future of integrating technology with language?


Speaker Biography

Li Yan is an Associate Professor at the Institute of Language Sciences, Shanghai International Studies University, and a Senior Artificial Intelligence Engineer. She teaches core courses such as Business IntelligenceManagement Information SystemsMachine LearningKnowledge GraphsPython Programming and Data Analysis, and Advanced Mathematics. She has published multiple SCI-indexed papers. She has led projects funded by the National Natural Science Foundation of China, sub-projects of Major Projects of the National Social Science Fund, and the Special Fund for Outstanding Young University Teachers of Shanghai. She has also been awarded multiple industry-sponsored research projects from the Shanghai Development and Reform Commission, Shanghai Yuankai Group, and China State Shipbuilding Corporation. Her honors include an International Paper Award, a National Outstanding Case Award, recognition as a Core Faculty Member, and the title of March 8th Red Banner Pacesetter at Shanghai International Studies University.


Abstract

In recent years, large language models have attracted widespread attention from language researchers, yet how to use them appropriately remains a topic for discussion. This lecture traces the “past” and “present” of large language models to help language researchers make better use of these tools. Drawing on recent research cases from our research group, it explores the integration of artificial intelligence technology with language research.


Join us on December 17 at 13:30 in Room 5103, Teaching Building No. 5!