404 citations · 509 across the 7 of their papers we have counts for
4 papers · 1 filter
Generating Negative Samples for Sequential Recommendation
Yongjun Chen, Jia Li, Zhiwei Liu +4
To make Sequential Recommendation (SR) successful, recent works focus on designing effective sequential encoders, fusing side information, and mining extra positive self-supervisio…
ELECRec: Training Sequential Recommenders as Discriminators
Yongjun Chen, Jia Li, Caiming Xiong
Sequential recommendation is often considered as a generative task, i.e., training a sequential encoder to generate the next item of a user's interests based on her historical inte…
Improving Contrastive Learning with Model Augmentation
Zhiwei Liu, Yongjun Chen, Jia Li +3
The sequential recommendation aims at predicting the next items in user behaviors, which can be solved by characterizing item relationships in sequences. Due to the data sparsity a…
Intent Contrastive Learning for Sequential Recommendation
Yongjun Chen, Zhiwei Liu, Jia Li +2
Users' interactions with items are driven by various intents (e.g., preparing for holiday gifts, shopping for fishing equipment, etc.).However, users' underlying intents are often…