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

doi:10.1145/3711896.3737869

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

College of Information Sciences and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Publisher	Association for Computing Machinery
Pages	6278-6279
Number of pages	2
ISBN (Electronic)	9798400714542
DOIs	https://doi.org/10.1145/3711896.3737869
State	Published - Aug 3 2025
Event	31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025 - Toronto, Canada Duration: Aug 3 2025 → Aug 7 2025

Publication series

Name	Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Volume	2
ISSN (Print)	2154-817X

Conference

Conference	31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025
Country/Territory	Canada
City	Toronto
Period	8/3/25 → 8/7/25

All Science Journal Classification (ASJC) codes

Software
Information Systems

Access to Document

10.1145/3711896.3737869

Cite this

Han, H., Wang, F., Luo, C., Liu, H., Huang, J., Li, Z., Dai, Z., He, Q., Sun, Y., Yin, D., Wang, S., Tang, J., Pei, J., & Tang, X. (2025). The 2nd Workshop on Large Language Models for E-Commerce. In KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 6278-6279). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. 2). Association for Computing Machinery. https://doi.org/10.1145/3711896.3737869

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title = "The 2nd Workshop on Large Language Models for E-Commerce",

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.",

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

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doi = "10.1145/3711896.3737869",

language = "English (US)",

series = "Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",

publisher = "Association for Computing Machinery",

pages = "6278--6279",

booktitle = "KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining",

}

Han, H, Wang, F, Luo, C, Liu, H, Huang, J, Li, Z, Dai, Z, He, Q, Sun, Y, Yin, D, Wang, S, Tang, J, Pei, J & Tang, X 2025, The 2nd Workshop on Large Language Models for E-Commerce. in KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, vol. 2, Association for Computing Machinery, pp. 6278-6279, 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025, Toronto, Canada, 8/3/25. https://doi.org/10.1145/3711896.3737869

The 2nd Workshop on Large Language Models for E-Commerce. / Han, Haoyu; Wang, Fali; Luo, Chen et al.
KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, 2025. p. 6278-6279 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Sun, Yiwei

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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.

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Han H, Wang F, Luo C, Liu H, Huang J, Li Z et al. The 2nd Workshop on Large Language Models for E-Commerce. In KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery. 2025. p. 6278-6279. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). doi: 10.1145/3711896.3737869

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

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All Science Journal Classification (ASJC) codes

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