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20182026
most citedRobust Preference-Guided Denoising for Graph based Social Recommendation

83 citations · 85 across the 5 of their papers we have counts for

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cs.IR2026

Tlow: Flow-based Item Tokenizer for Recommendation

Nian Li, Chonggang Song, Jingtao Ding +3

Item tokenizer encodes semantic embeddings into token IDs to replace the randomly assigned item IDs used in traditional recommendation models, fundamentally addressing the problems…

cs.IR2023

Alleviating Video-Length Effect for Micro-video Recommendation

Yuhan Quan, Jingtao Ding, Chen Gao +4

Micro-videos platforms such as TikTok are extremely popular nowadays. One important feature is that users no longer select interested videos from a set, instead they either watch t…

cs.IR2023

Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering

Yan Wen, Chen Gao, Lingling Yi +3

Automated Machine Learning (AutoML) techniques have recently been introduced to design Collaborative Filtering (CF) models in a data-specific manner. However, existing works either…

cs.IR202383 cited

Robust Preference-Guided Denoising for Graph based Social Recommendation

Yuhan Quan, Jingtao Ding, Chen Gao +3

Graph Neural Network(GNN) based social recommendation models improve the prediction accuracy of user preference by leveraging GNN in exploiting preference similarity contained in s…

cs.IR2020

SocialTrans: A Deep Sequential Model with Social Information for Web-Scale Recommendation Systems

Qiaoan Chen, Hao Gu, Lingling Yi +4

On social network platforms, a user's behavior is based on his/her personal interests, or influenced by his/her friends. In the literature, it is common to model either users' pers…