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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

Showing 126150 of 554 papers

TitleStatusHype
Is Contrastive Learning Necessary? A Study of Data Augmentation vs Contrastive Learning in Sequential RecommendationCode1
Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate PredictionCode1
Self-Attentive Sequential RecommendationCode1
Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential RecommendationCode1
EAGER: Two-Stream Generative Recommender with Behavior-Semantic CollaborationCode1
Data Augmentation as Free Lunch: Exploring the Test-Time Augmentation for Sequential RecommendationCode1
An Attentive Inductive Bias for Sequential Recommendation beyond the Self-AttentionCode1
Debiased Contrastive Learning for Sequential RecommendationCode1
Debiasing Sequential Recommenders through Distributionally Robust Optimization over System ExposureCode1
Debiasing the Cloze Task in Sequential Recommendation with Bidirectional TransformersCode1
Decoupled Side Information Fusion for Sequential RecommendationCode1
Linear Recurrent Units for Sequential RecommendationCode1
Linear-Time Self Attention with Codeword Histogram for Efficient RecommendationCode1
An Empirical Study of Training ID-Agnostic Multi-modal Sequential RecommendersCode1
Dually Enhanced Propensity Score Estimation in Sequential RecommendationCode1
Diffusion-based Contrastive Learning for Sequential RecommendationCode1
Dynamic Graph Neural Networks for Sequential RecommendationCode1
ELECRec: Training Sequential Recommenders as DiscriminatorsCode1
EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph LearningCode1
Determinantal Point Process Likelihoods for Sequential RecommendationCode1
SIGMA: Selective Gated Mamba for Sequential RecommendationCode1
DIFF: Dual Side-Information Filtering and Fusion for Sequential RecommendationCode1
DiffuRec: A Diffusion Model for Sequential RecommendationCode1
Diffusion Augmentation for Sequential RecommendationCode1
Leveraging Large Language Models for Sequential RecommendationCode1
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