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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 151–175 of 554 papers

TitleStatusHype
APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential RecommendationCode1
Generative Recommender with End-to-End Learnable Item TokenizationCode1
An Attentive Inductive Bias for Sequential Recommendation beyond the Self-AttentionCode1
LLaRA: Large Language-Recommendation AssistantCode1
Ada-Ranker: A Data Distribution Adaptive Ranking Paradigm for Sequential RecommendationCode1
FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation LearningCode1
Graph Masked Autoencoder for Sequential RecommendationCode1
MARS: Matching Attribute-aware Representations for Text-based Sequential RecommendationCode1
Explanation Guided Contrastive Learning for Sequential RecommendationCode1
Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate PredictionCode1
Mixed Attention Network for Cross-domain Sequential RecommendationCode1
Mixed Information Flow for Cross-domain Sequential RecommendationsCode1
Evaluating Performance and Bias of Negative Sampling in Large-Scale Sequential Recommendation ModelsCode1
Hierarchical Time-Aware Mixture of Experts for Multi-Modal Sequential RecommendationCode1
KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed VideosCode1
CT4Rec: Simple yet Effective Consistency Training for Sequential RecommendationCode1
Meta-optimized Contrastive Learning for Sequential RecommendationCode1
Dynamic Graph Neural Networks for Sequential RecommendationCode1
Dynamic Memory based Attention Network for Sequential RecommendationCode1
E4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential RecommendationCode1
EAGER: Two-Stream Generative Recommender with Behavior-Semantic CollaborationCode1
EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph LearningCode1
Exploring Periodicity and Interactivity in Multi-Interest Framework for Sequential RecommendationCode1
Pacer and Runner: Cooperative Learning Framework between Single- and Cross-Domain Sequential RecommendationCode1
Relative Contrastive Learning for Sequential Recommendation with Similarity-based Positive Pair SelectionCode1
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