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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 401–450 of 554 papers

TitleStatusHype
HTP: Exploiting Holistic Temporal Patterns for Sequential RecommendationCode0
AdaptiveRec: Adaptively Construct Pairs for Contrastive Learning in Sequential Recommendation—0
Fisher-Weighted Merge of Contrastive Learning Models in Sequential Recommendation—0
G-STO: Sequential Main Shopping Intention Detection via Graph-Regularized Stochastic Transformer—0
Sequential Recommendation with Controllable Diversification: Representation Degeneration and DiversityCode0
Generative Sequential Recommendation with GPTRec—0
Neighborhood-based Hard Negative Mining for Sequential RecommendationCode0
Robust Reinforcement Learning Objectives for Sequential Recommender SystemsCode0
TriMLP: Revenge of a MLP-like Architecture in Sequential RecommendationCode0
PALR: Personalization Aware LLMs for Recommendation—0
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
Conditional Denoising Diffusion for Sequential Recommendation—0
Sequential Recommendation with Probabilistic Logical ReasoningCode0
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
Multimodal Pre-training Framework for Sequential Recommendation via Contrastive Learning—0
GUESR: A Global Unsupervised Data-Enhancement with Bucket-Cluster Sampling for Sequential Recommendation—0
Meta-Learning with Adaptive Weighted Loss for Imbalanced Cold-Start RecommendationCode0
Intelligent Model Update Strategy for Sequential Recommendation—0
On Modeling Long-Term User Engagement from Stochastic Feedback—0
Dual-interest Factorization-heads Attention for Sequential RecommendationCode0
Towards Lightweight Cross-domain Sequential Recommendation via External Attention-enhanced Graph Convolution NetworkCode0
Modeling Sequential Recommendation as Missing Information ImputationCode0
Improving Sequential Recommendation Models with an Enhanced Loss FunctionCode0
Local Policy Improvement for Recommender Systems—0
Denoising Self-attentive Sequential Recommendation—0
Equivariant Contrastive Learning for Sequential RecommendationCode0
One Person, One Model--Learning Compound Router for Sequential RecommendationCode0
Self-Attentive Sequential Recommendation with Cheap Causal Convolutions—0
Disentangling Past-Future Modeling in Sequential Recommendation via Dual NetworksCode0
Sequential Recommendation with Auxiliary Item Relationships via Multi-Relational TransformerCode0
Understanding or Manipulation: Rethinking Online Performance Gains of Modern Recommender Systems—0
DDGHM: Dual Dynamic Graph with Hybrid Metric Training for Cross-Domain Sequential Recommendation—0
Mutual Harmony: Sequential Recommendation with Dual Contrastive NetworkCode0
PARSRec: Explainable Personalized Attention-fused Recurrent Sequential Recommendation Using Session Partial ActionsCode0
Recursive Attentive Methods with Reused Item Representations for Sequential Recommendation—0
Beyond Double Ascent via Recurrent Neural Tangent Kernel in Sequential RecommendationCode0
Multi-level Contrastive Learning Framework for Sequential Recommendation—0
Towards Communication Efficient and Fair Federated Personalized Sequential Recommendation—0
Improving Micro-video Recommendation by Controlling Position Bias—0
IDNP: Interest Dynamics Modeling using Generative Neural Processes for Sequential Recommendation—0
Time Lag Aware Sequential Recommendation—0
UFNRec: Utilizing False Negative Samples for Sequential RecommendationCode0
Sparse Attentive Memory Network for Click-through Rate Prediction with Long SequencesCode0
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