2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.IR2024
Denoising Time Cycle Modeling for Recommendation
Sicong Xie, Qunwei Li, Weidi Xu +3
Recently, modeling temporal patterns of user-item interactions have attracted much attention in recommender systems. We argue that existing methods ignore the variety of temporal p…
cs.IR2022★ 2 cited
Prototypical Contrastive Learning and Adaptive Interest Selection for Candidate Generation in Recommendations
Ningning Li, Qunwei Li, Xichen Ding +2
Deep Candidate Generation plays an important role in large-scale recommender systems. It takes user history behaviors as inputs and learns user and item latent embeddings for candi…
cs.AI2022
Device-Cloud Collaborative Recommendation via Meta Controller
Jiangchao Yao, Feng Wang, Xichen Ding +4
On-device machine learning enables the lightweight deployment of recommendation models in local clients, which reduces the burden of the cloud-based recommenders and simultaneously…