1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.IR2025
OneTrans: Unified Feature Interaction and Sequence Modeling with One Transformer in Industrial Recommender
Zhaoqi Zhang, Haolei Pei, Jun Guo +5
In recommendation systems, scaling up feature-interaction modules (e.g., Wukong, RankMixer) or user-behavior sequence modules (e.g., LONGER) has achieved notable success. However,…
cs.AI2023★ 1 cited
Clustered Embedding Learning for Recommender Systems
Yizhou Chen, Guangda Huzhang, Anxiang Zeng +7
In recent years, recommender systems have advanced rapidly, where embedding learning for users and items plays a critical role. A standard method learns a unique embedding vector f…