438 citations · 833 across the 19 of their papers we have counts for
7 papers · 1 filter
Whole Page Unbiased Learning to Rank
Haitao Mao, Lixin Zou, Yujia Zheng +5
The page presentation biases in the information retrieval system, especially on the click behavior, is a well-known challenge that hinders improving ranking models' performance wit…
Factorized and Controllable Neural Re-Rendering of Outdoor Scene for Photo Extrapolation
Boming Zhao, Bangbang Yang, Zhenyang Li +6
Expanding an existing tourist photo from a partially captured scene to a full scene is one of the desired experiences for photography applications. Although photo extrapolation has…
Hypergraph Contrastive Collaborative Filtering
Lianghao Xia, Chao Huang, Yong Xu +3
Collaborative Filtering (CF) has emerged as fundamental paradigms for parameterizing users and items into latent representation space, with their correlative patterns from interact…
Sequential Recommendation with User Evolving Preference Decomposition
Weiqi Shao, Xu Chen, Long Xia +2
Modeling user sequential behaviors has recently attracted increasing attention in the recommendation domain. Existing methods mostly assume coherent preference in the same sequence…
Contrastive Meta Learning with Behavior Multiplicity for Recommendation
Wei Wei, Chao Huang, Lianghao Xia +3
A well-informed recommendation framework could not only help users identify their interested items, but also benefit the revenue of various online platforms (e.g., e-commerce, soci…
User behavior understanding in real world settings
Weiqi Shao, Xu Chen, Jiashu Zhao +2
How to extract meaningful information in user historical behavior plays a crucial role in recommendation. User behavior sequence often contains multiple conceptually distinct items…
Gumble Softmax For User Behavior Modeling
Weiqi Shao, Xu Chen, Jiashu Zhao +2
Recently, sequential recommendation systems are important in solving the information overload in many online services. Current methods in sequential recommendation focus on learnin…