Year: 2025
Type: conference-paper
Abstract: Large Language Models (LLMs) are transforming E-Commerce by powering numerous applications such as product recommendation, search, classification, question answering, and advertising. Their growing adoption in real-world systems highlights their potential, yet challenges remain in ensuring accuracy, efficiency, fairness, and privacy. This workshop aims to bring together researchers and industry practitioners to explore the opportunities and limitations of LLMs in e-commerce. Through discussions on model design, algorithmic advancements, and practical deployment strategies, the workshop seeks to foster collaboration, bridge the gap between academia and industry, and drive innovation in applying LLMs to E-Commerce.
Authors: Haoyu Han, Xianfeng Tang, Jing Huang, Monica Cheng, Omar Alonso, Hanqing Lu, Zhen Li, Chen Luo, Dawei Yin, Jiliang Tang
Institutions: Michigan State University, Amazon (United States), Baidu (China)
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4411549842