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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 1–50 of 554 papers

TitleStatusHype
Similarity-Guided Diffusion for Contrastive Sequential Recommendation—0
Unconditional Diffusion for Generative Sequential RecommendationCode0
FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential RecommendationCode1
DARTS: A Dual-View Attack Framework for Targeted Manipulation in Federated Sequential Recommendation—0
A Systematic Replicability and Comparative Study of BSARec and SASRec for Sequential Recommendation—0
LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential RecommendationCode2
C-TLSAN: Content-Enhanced Time-Aware Long- and Short-Term Attention Network for Personalized RecommendationCode0
RecGPT: A Foundation Model for Sequential RecommendationCode2
GLoSS: Generative Language Models with Semantic Search for Sequential RecommendationCode1
Unlocking the Power of Diffusion Models in Sequential Recommendation: A Simple and Effective ApproachCode1
Semantic-enhanced Co-attention Prompt Learning for Non-overlapping Cross-Domain RecommendationCode0
Flow Matching based Sequential Recommender ModelCode1
LARES: Latent Reasoning for Sequential Recommendation—0
DIFF: Dual Side-Information Filtering and Fusion for Sequential RecommendationCode1
HMamba: Hyperbolic Mamba for Sequential Recommendation—0
M2Rec: Multi-scale Mamba for Efficient Sequential Recommendation—0
STAR-Rec: Making Peace with Length Variance and Pattern Diversity in Sequential Recommendation—0
A Framework for Elastic Adaptation of User Multiple Intents in Sequential Recommendation—0
X-Cross: Dynamic Integration of Language Models for Cross-Domain Sequential Recommendation—0
AlphaFuse: Learn ID Embeddings for Sequential Recommendation in Null Space of Language EmbeddingsCode1
Relative Contrastive Learning for Sequential Recommendation with Similarity-based Positive Pair SelectionCode1
Bridge the Domains: Large Language Models Enhanced Cross-domain Sequential Recommendation—0
Intent-aware Diffusion with Contrastive Learning for Sequential RecommendationCode1
Hierarchical Attention Fusion of Visual and Textual Representations for Cross-Domain Sequential Recommendation—0
Adaptive Long-term Embedding with Denoising and Augmentation for RecommendationCode0
Improving Sequential Recommenders through Counterfactual Augmentation of System ExposureCode0
Improving LLM Interpretability and Performance via Guided Embedding Refinement for Sequential Recommendation—0
CROSSAN: Towards Efficient and Effective Adaptation of Multiple Multimodal Foundation Models for Sequential RecommendationCode0
Slow Thinking for Sequential Recommendation—0
Revisiting Self-Attentive Sequential RecommendationCode4
JEPA4Rec: Learning Effective Language Representations for Sequential Recommendation via Joint Embedding Predictive Architecture—0
A Novel Mamba-based Sequential Recommendation Method—0
BBQRec: Behavior-Bind Quantization for Multi-Modal Sequential Recommendation—0
Diversity-aware Dual-promotion Poisoning Attack on Sequential Recommendation—0
Data Augmentation as Free Lunch: Exploring the Test-Time Augmentation for Sequential RecommendationCode1
AdaptRec: A Self-Adaptive Framework for Sequential Recommendations with Large Language Models—0
Test-Time Alignment for Tracking User Interest Shifts in Sequential Recommendation—0
Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement LearningCode2
Filtering with Time-frequency Analysis: An Adaptive and Lightweight Model for Sequential Recommender Systems Based on Discrete Wavelet Transform—0
Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation—0
Learnable Sequence Augmenter for Triplet Contrastive Learning in Sequential Recommendation—0
Recommendation System in Advertising and Streaming Media: Unsupervised Data Enhancement Sequence Suggestions—0
Federated Mixture-of-Expert for Non-Overlapped Cross-Domain Sequential Recommendation—0
LLMSeR: Enhancing Sequential Recommendation via LLM-based Data Augmentation—0
Bridging Textual-Collaborative Gap through Semantic Codes for Sequential Recommendation—0
Benchmarking LLMs in Recommendation Tasks: A Comparative Evaluation with Conventional Recommenders—0
Semantic Retrieval Augmented Contrastive Learning for Sequential Recommendation—0
HeterRec: Heterogeneous Information Transformer for Scalable Sequential Recommendation—0
Semantic Gaussian Mixture Variational Autoencoder for Sequential RecommendationCode0
Lightweight yet Efficient: An External Attentive Graph Convolutional Network with Positional Prompts for Sequential RecommendationCode0
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