Research paper

EAGER: Enrich-and-Align Generative Query Recommendation from Clicked Items in E-commerce Search

Research from AlibabaPublished by Association for Computational LinguisticsOct 2026PDF

See how the products a shopper clicks can inform better suggestions for their next search query.

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Shuwei Yuan, Mingqian Ding, Luxin Liu, Rong Xiao, Xiaoyi Zeng. EAGER: Enrich-and-Align Generative Query Recommendation from Clicked Items in E-commerce Search. Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track. © 2026 Association for Computational Linguistics. CC BY 4.0. 10.18653/2026.emnlp-industry.111. Original PDF, unmodified.

CC BY 4.0

EAGER: Enrich-and-Align Generative Query Recommendation from Clicked Items in E-commerce Search

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