Turnitin
降AI改写
早检测系统
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Grammarly检测
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Diffusion recommender model
Generative models such as Generative Adversarial Networks (GANs) and Variational Auto-
Encoders (VAEs) are widely utilized to model the generative process of user interactions …
Encoders (VAEs) are widely utilized to model the generative process of user interactions …
Aligning distillation for cold-start item recommendation
Recommending cold items in recommendation systems is a longstanding challenge due to
the inherent differences between warm items, which are recommended based on user …
the inherent differences between warm items, which are recommended based on user …
Macro graph neural networks for online billion-scale recommender systems
Predicting Click-Through Rate (CTR) in billion-scale recommender systems poses a long-
standing challenge for Graph Neural Networks (GNNs) due to the overwhelming …
standing challenge for Graph Neural Networks (GNNs) due to the overwhelming …
Opengraph: Towards open graph foundation models
L ** users: cross-domain recommendation via adaptive anchor link learning
Cross-Domain Recommendation (CDR) is capable of incorporating auxiliary information
from multiple domains to advance recommendation performance. Conventional CDR …
from multiple domains to advance recommendation performance. Conventional CDR …
Recdiff: diffusion model for social recommendation
Social recommendation has emerged as a powerful approach to enhance personalized
recommendations by leveraging the social connections among users, such as following and …
recommendations by leveraging the social connections among users, such as following and …
Adaptive popularity debiasing aggregator for graph collaborative filtering
The graph neural network-based collaborative filtering (CF) models user-item interactions as
a bipartite graph and performs iterative aggregation to enhance performance. Unfortunately …
a bipartite graph and performs iterative aggregation to enhance performance. Unfortunately …