99 citations · 352 across the 29 of their papers we have counts for
4 papers · 1 filter
Could Small Language Models Serve as Recommenders? Towards Data-centric Cold-start Recommendations
Xuansheng Wu, Huachi Zhou, Yucheng Shi +3
Recommendation systems help users find matched items based on their previous behaviors. Personalized recommendation becomes challenging in the absence of historical user-item inter…
Dynamic Memory based Attention Network for Sequential Recommendation
Qiaoyu Tan, Jianwei Zhang, Ninghao Liu +4
Sequential recommendation has become increasingly essential in various online services. It aims to model the dynamic preferences of users from their historical interactions and pre…
Sparse-Interest Network for Sequential Recommendation
Qiaoyu Tan, Jianwei Zhang, Jiangchao Yao +4
Recent methods in sequential recommendation focus on learning an overall embedding vector from a user's behavior sequence for the next-item recommendation. However, from empirical…
Learning to Hash with Graph Neural Networks for Recommender Systems
Qiaoyu Tan, Ninghao Liu, Xing Zhao +3
Graph representation learning has attracted much attention in supporting high quality candidate search at scale. Despite its effectiveness in learning embedding vectors for objects…