Large Language Model for E-Commerce Workshop
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
- Monica Cheng (ORCID: https://orcid.org/0000-0002-1140-687X)
- Jiliang Tang (ORCID: https://orcid.org/0000-0001-7125-3898)
- Omar Alonso (ORCID: https://orcid.org/0009-0009-2515-4771)
- Zhen Li (ORCID: https://orcid.org/0009-0008-1247-0284)
- Jing‐Zhi Huang (ORCID: https://orcid.org/0000-0001-8769-9130)
- Hanqing Lu (ORCID: https://orcid.org/0000-0001-9506-3407)
- Dawei Yin (ORCID: https://orcid.org/0000-0002-0684-6205)
- Haoyu Han (ORCID: https://orcid.org/0000-0002-2529-6042)
- Xianfeng Tang (ORCID: https://orcid.org/0000-0003-1554-2761)
- Chen Luo (ORCID: https://orcid.org/0000-0001-5339-5817)
Institutions
- Amazon (United States) (US)
- Michigan State University (US)
- Baidu (China) (CN)
Publication Details
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1145/3701716.3717864
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00