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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 1–25 of 554 papers

TitleStatusHype
Revisiting Self-Attentive Sequential RecommendationCode4
HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User ModelingCode4
Data Augmentation for Sequential Recommendation: A SurveyCode3
LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential RecommendationCode2
RecGPT: A Foundation Model for Sequential RecommendationCode2
Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement LearningCode2
LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential RecommendationCode2
LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential RecommendationCode2
SelfGNN: Self-Supervised Graph Neural Networks for Sequential RecommendationCode2
Dataset Regeneration for Sequential RecommendationCode2
Multi-Behavior Generative RecommendationCode2
IDGenRec: LLM-RecSys Alignment with Textual ID LearningCode2
Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space ModelsCode2
MACRec: a Multi-Agent Collaboration Framework for RecommendationCode2
Improving Sequential Recommendations with LLMsCode2
End-to-end Learnable Clustering for Intent Learning in RecommendationCode2
SSLRec: A Self-Supervised Learning Framework for RecommendationCode2
OpenP5: An Open-Source Platform for Developing, Training, and Evaluating LLM-based Recommender SystemsCode2
Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)Code2
RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation AlgorithmsCode2
FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential RecommendationCode1
GLoSS: Generative Language Models with Semantic Search for Sequential RecommendationCode1
Unlocking the Power of Diffusion Models in Sequential Recommendation: A Simple and Effective ApproachCode1
Flow Matching based Sequential Recommender ModelCode1
DIFF: Dual Side-Information Filtering and Fusion for Sequential RecommendationCode1
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