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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 76100 of 554 papers

TitleStatusHype
RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k RecommendationCode1
An Attentive Inductive Bias for Sequential Recommendation beyond the Self-AttentionCode1
Context-Aware Sequential Model for Multi-Behaviour RecommendationCode1
Debiasing Sequential Recommenders through Distributionally Robust Optimization over System ExposureCode1
RecJPQ: Training Large-Catalogue Sequential RecommendersCode1
LLaRA: Large Language-Recommendation AssistantCode1
E4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential RecommendationCode1
Collaborative Word-based Pre-trained Item Representation for Transferable RecommendationCode1
Mixed Attention Network for Cross-domain Sequential RecommendationCode1
Rethinking Cross-Domain Sequential Recommendation under Open-World AssumptionsCode1
APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential RecommendationCode1
Generate What You Prefer: Reshaping Sequential Recommendation via Guided DiffusionCode1
Large Language Model Can Interpret Latent Space of Sequential RecommenderCode1
Intent Contrastive Learning with Cross Subsequences for Sequential RecommendationCode1
To Copy, or not to Copy; That is a Critical Issue of the Output Softmax Layer in Neural Sequential RecommendersCode1
Linear Recurrent Units for Sequential RecommendationCode1
KuaiSim: A Comprehensive Simulator for Recommender SystemsCode1
Diffusion Augmentation for Sequential RecommendationCode1
Leveraging Large Language Models for Sequential RecommendationCode1
FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation LearningCode1
Adaptive Multi-Modalities Fusion in Sequential Recommendation SystemsCode1
Text Matching Improves Sequential Recommendation by Reducing Popularity BiasesCode1
LLMRec: Benchmarking Large Language Models on Recommendation TaskCode1
MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for RecommendationCode1
Attention Calibration for Transformer-based Sequential RecommendationCode1
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