1 citations · 1 across the 4 of their papers we have counts for
4 papers
A Bird's-eye View of Reranking: from List Level to Page Level
Yunjia Xi, Jianghao Lin, Weiwen Liu +5
Reranking, as the final stage of multi-stage recommender systems, refines the initial lists to maximize the total utility. With the development of multimedia and user interface des…
Multi-Level Interaction Reranking with User Behavior History
Yunjia Xi, Weiwen Liu, Jieming Zhu +6
As the final stage of the multi-stage recommender system (MRS), reranking directly affects users' experience and satisfaction, thus playing a critical role in MRS. Despite the impr…
PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation
Yi Li, Jieming Zhu, Weiwen Liu +6
The goal of recommender systems is to provide ordered item lists to users that best match their interests. As a critical task in the recommendation pipeline, re-ranking has receive…
Neural Re-ranking in Multi-stage Recommender Systems: A Review
Weiwen Liu, Yunjia Xi, Jiarui Qin +5
As the final stage of the multi-stage recommender system (MRS), re-ranking directly affects user experience and satisfaction by rearranging the input ranking lists, and thereby pla…