TY - GEN
T1 - The 2nd Workshop on Large Language Models for E-Commerce
AU - Han, Haoyu
AU - Wang, Fali
AU - Luo, Chen
AU - Liu, Hui
AU - Huang, Jing
AU - Li, Zhen
AU - Dai, Zhenwei
AU - He, Qi
AU - Sun, Yiwei
AU - Yin, Dawei
AU - Wang, Suhang
AU - Tang, Jiliang
AU - Pei, Jian
AU - Tang, Xianfeng
N1 - Publisher Copyright:
© 2025 Owner/Author.
PY - 2025/8/3
Y1 - 2025/8/3
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/105014323209
UR - https://www.scopus.com/inward/citedby.url?scp=105014323209&partnerID=8YFLogxK
U2 - 10.1145/3711896.3737869
DO - 10.1145/3711896.3737869
M3 - Conference contribution
AN - SCOPUS:105014323209
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 6278
EP - 6279
BT - KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining
PB - Association for Computing Machinery
T2 - 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025
Y2 - 3 August 2025 through 7 August 2025
ER -