3 papers
cs.IR2026
OneTrans-V2: Unifying Retrieval, Pre-rank, and Fine-rank with One Transformer in Industrial Recommender
Hannan Cao, Jun Guo, Haolei Pei +18
Industrial recommendation systems typically operate as a \emph{cascade} of retrieval, pre-rank, and fine-rank, but these stages are usually trained and served as separate models, c…
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.IR2024
RimiRec: Modeling Refined Multi-interest in Hierarchical Structure for Recommendation
Haolei Pei, Yuanyuan Xu, Yangping Zhu +1
Industrial recommender systems usually consist of the retrieval stage and the ranking stage, to handle the billion-scale of users and items. The retrieval stage retrieves candidate…