The 2nd Workshop on Large Language Models for E-Commerce

Haoyu Han, Fali Wang, Chen Luo, Hui Liu, Jing Huang, Zhen Li, Zhenwei Dai, Qi He, Yiwei Sun, Dawei Yin, Suhang Wang, Jiliang Tang, Jian Pei, Xianfeng Tang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Large Language Models (LLMs) are revolutionizing E-Commerce by enabling product recommendation, search, classification, question answering, and advertising applications. Their increasing adoption in real-world systems underscores their potential; however, challenges persist in ensuring accuracy, efficiency, fairness, and privacy. This workshop aims to bring together researchers and industry practitioners to explore both the limitations and opportunities of LLMs in e-commerce. The workshop seeks to foster collaboration, bridge the gap between academia and industry, and drive innovation in the application of LLMs to E-Commerce through discussions on model design, algorithmic advancements, and practical deployment.

Original languageEnglish (US)
Title of host publicationKDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining
PublisherAssociation for Computing Machinery
Pages6278-6279
Number of pages2
ISBN (Electronic)9798400714542
DOIs
StatePublished - Aug 3 2025
Event31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025 - Toronto, Canada
Duration: Aug 3 2025Aug 7 2025

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Volume2
ISSN (Print)2154-817X

Conference

Conference31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025
Country/TerritoryCanada
CityToronto
Period8/3/258/7/25

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems

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