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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 301–350 of 554 papers

TitleStatusHype
Beyond Inter-Item Relations: Dynamic Adaption for Enhancing LLM-Based Sequential Recommendation—0
Calibration-Disentangled Learning and Relevance-Prioritized Reranking for Calibrated Sequential RecommendationCode0
Exploiting Preferences in Loss Functions for Sequential Recommendation via Weak Transitivity—0
Semantic Codebook Learning for Dynamic Recommendation Models—0
GenRec: Generative Sequential Recommendation with Large Language ModelsCode0
Enhancing CTR Prediction through Sequential Recommendation Pre-training: Introducing the SRP4CTR Framework—0
MaTrRec: Uniting Mamba and Transformer for Sequential RecommendationCode0
Sample Enrichment via Temporary Operations on Subsequences for Sequential Recommendation—0
Denoising Long- and Short-term Interests for Sequential Recommendation—0
MLSA4Rec: Mamba Combined with Low-Rank Decomposed Self-Attention for Sequential Recommendation—0
SEMINAR: Search Enhanced Multi-modal Interest Network and Approximate Retrieval for Lifelong Sequential RecommendationCode0
Preference Distillation for Personalized Generative RecommendationCode0
Learning Positional Attention for Sequential RecommendationCode0
Behavior-Dependent Linear Recurrent Units for Efficient Sequential RecommendationCode0
DELRec: Distilling Sequential Pattern to Enhance LLMs-based Sequential RecommendationCode0
DIET: Customized Slimming for Incompatible Networks in Sequential Recommendation—0
PTF-FSR: A Parameter Transmission-Free Federated Sequential Recommender SystemCode0
GLINT-RU: Gated Lightweight Intelligent Recurrent Units for Sequential Recommender Systems—0
Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential RecommendationCode0
EchoMamba4Rec: Harmonizing Bidirectional State Space Models with Spectral Filtering for Advanced Sequential RecommendationCode0
Your Causal Self-Attentive Recommender Hosts a Lonely NeighborhoodCode0
Towards commands recommender system in BIM authoring tool using transformers—0
A Practice-Friendly LLM-Enhanced Paradigm with Preference Parsing for Sequential Recommendation—0
Information Maximization via Variational Autoencoders for Cross-Domain Recommendation—0
Attention-based sequential recommendation system using multimodal data—0
Look into the Future: Deep Contextualized Sequential Recommendation—0
Learning Partially Aligned Item Representation for Cross-Domain Sequential Recommendation—0
Positional encoding is not the same as context: A study on positional encoding for sequential recommendationCode0
ID-centric Pre-training for Recommendation—0
Improve Temporal Awareness of LLMs for Sequential Recommendation—0
CALRec: Contrastive Alignment of Generative LLMs for Sequential Recommendation—0
Are We Really Achieving Better Beyond-Accuracy Performance in Next Basket Recommendation?—0
Contrastive Learning Method for Sequential Recommendation based on Multi-Intention Disentanglement—0
TruthSR: Trustworthy Sequential Recommender Systems via User-generated Multimodal ContentCode0
CoST: Contrastive Quantization based Semantic Tokenization for Generative Recommendation—0
Multi-Level Sequence Denoising with Cross-Signal Contrastive Learning for Sequential RecommendationCode0
Beyond the Sequence: Statistics-Driven Pre-training for Stabilizing Sequential Recommendation Model—0
RecGPT: Generative Personalized Prompts for Sequential Recommendation via ChatGPT Training Paradigm—0
Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term RetentionCode0
END4Rec: Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation—0
Reinforcement Learning-based Recommender Systems with Large Language Models for State Reward and Action Modeling—0
Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential RecommendationCode0
Context-based Fast Recommendation Strategy for Long User Behavior Sequence in Meituan Waimai—0
The Whole is Better than the Sum: Using Aggregated Demonstrations in In-Context Learning for Sequential RecommendationCode0
Empowering Sequential Recommendation from Collaborative Signals and Semantic RelatednessCode0
Multi-Tower Multi-Interest Recommendation with User Representation Repel—0
Aligning GPTRec with Beyond-Accuracy Goals with Reinforcement LearningCode0
Can Small Language Models be Good Reasoners for Sequential Recommendation?—0
BiVRec: Bidirectional View-based Multimodal Sequential Recommendation—0
BMLP: Behavior-aware MLP for Heterogeneous Sequential Recommendation—0
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