2 citations · 2 across the 4 of their papers we have counts for
4 papers
EAGER: Enrich-and-Align Generative Query Recommendation from Clicked Items in E-commerce Search
Shuwei Yuan, Mingqian Ding, Luxin Liu +2
E-commerce platforms increasingly display clickable query suggestions alongside items in the user feed, enabling users to refine or expand their intent without manually reformulati…
SAM-D2Q: Aligning Multimodal Doc2Query with Search Demand and Conversion for E-commerce
Hui Zhou, Jian Hui Ji, Lei Ma +2
E-commerce search often suffers from vocabulary mismatch between user queries and merchant-authored product titles, since short titles cannot fully cover diverse user expressions o…
LLM-I2I: Boost Your Small Item2Item Recommendation Model with Large Language Model
Yinfu Feng, Yanjing Wu, Rong Xiao +1
Item-to-Item (I2I) recommendation models are widely used in real-world systems due to their scalability, real-time capabilities, and high recommendation quality. Research to enhanc…
ENCODE: Breaking the Trade-Off Between Performance and Efficiency in Long-Term User Behavior Modeling
Wenji Zhou, Yuhang Zheng, Yinfu Feng +5
Long-term user behavior sequences are a goldmine for businesses to explore users' interests to improve Click-Through Rate. However, it is very challenging to accurately capture use…