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Sequential Recommendation

Sequential recommendation is a sophisticated approach to providing personalized suggestions by analyzing users' historical interactions in a sequential manner. Unlike traditional recommendation systems, which consider items in isolation, sequential recommendation takes into account the temporal order of user actions. This method is particularly valuable in domains where the sequence of events matters, such as streaming services, e-commerce platforms, and social media.

Papers

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Showing 326–350 of 554 papers

TitleStatusHype
PALR: Personalization Aware LLMs for Recommendation—0
Graph Masked Autoencoder for Sequential RecommendationCode1
Contrastive Enhanced Slide Filter Mixer for Sequential RecommendationCode0
Attacking Pre-trained RecommendationCode0
Ensemble Modeling with Contrastive Knowledge Distillation for Sequential RecommendationCode0
Prediction then Correction: An Abductive Prediction Correction Method for Sequential RecommendationCode0
Self-Supervised Multi-Modal Sequential RecommendationCode1
Sequential Recommendation with Probabilistic Logical ReasoningCode0
Conditional Denoising Diffusion for Sequential Recommendation—0
Frequency Enhanced Hybrid Attention Network for Sequential RecommendationCode1
Attention Mixtures for Time-Aware Sequential RecommendationCode1
MELT: Mutual Enhancement of Long-Tailed User and Item for Sequential RecommendationCode1
Meta-optimized Contrastive Learning for Sequential RecommendationCode1
Learning Graph ODE for Continuous-Time Sequential Recommendation—0
Deep Stable Multi-Interest Learning for Out-of-distribution Sequential Recommendation—0
Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training—0
Sequential Recommendation with Diffusion Models—0
Automated Prompting for Non-overlapping Cross-domain Sequential Recommendation—0
Contrastive Cross-Domain Sequential RecommendationCode1
Zero-Shot Next-Item Recommendation using Large Pretrained Language ModelsCode1
DiffuRec: A Diffusion Model for Sequential RecommendationCode1
EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph LearningCode1
Multimodal Pre-training Framework for Sequential Recommendation via Contrastive Learning—0
Debiased Contrastive Learning for Sequential RecommendationCode1
Dually Enhanced Propensity Score Estimation in Sequential RecommendationCode1
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