mlsanityData to 7 Oct 2026

Sequential Recommender Systems: Challenges, Progress and Prospects

arXiv 2001.04830 ↗First posted 28 Dec 2019cs.IR cs.LGcited by 115

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Abstract (arXiv)

The emerging topic of sequential recommender systems has attracted increasing attention in recent years.Different from the conventional recommender systems including collaborative filtering and content-based filtering, SRSs try to understand and model the sequential user behaviors, the interactions between users and items, and the evolution of users preferences and item popularity over time. SRSs involve the above aspects for more precise characterization of user contexts, intent and goals, and item consumption trend, leading to more accurate, customized and dynamic recommendations.In this paper, we provide a systematic review on SRSs.We first present the characteristics of SRSs, and then summarize and categorize the key challenges in this research area, followed by the corresponding research progress consisting of the most recent and representative developments on this topic.Finally, we discuss the important research directions in this vibrant area.

Key facts. Cited by 115 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Dec 2019.

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Citing papers per year: 2021: 12; 2022: 19; 2023: 26; 2024: 27; 2025: 23; 2026: 8.

115 papers.

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  1. 2023User Behavior Simulation with Large Language Model based Agentscited by 136
  2. 2021Cross-Domain Recommendation: Challenges, Progress, and Prospectscited by 74
  3. 2024On Softmax Direct Preference Optimization for Recommendationcited by 64
  4. 2021Graph Learning based Recommender Systems: A Reviewcited by 59
  5. 2021Graph Trend Filtering Networks for Recommendationscited by 53
  6. 2025Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendationcited by 50
  7. 2024LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendationcited by 47
  8. 2023Diffusion Augmentation for Sequential Recommendationcited by 37
  9. 2024Customizing Language Models with Instance-wise LoRA for Sequential Recommendationcited by 32
  10. 2023MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendationcited by 30
  11. 2021Adversarial and Contrastive Variational Autoencoder for Sequential Recommendationcited by 28
  12. 2023A Survey on User Behavior Modeling in Recommender Systemscited by 26
38 more
  1. 2023AutoMLP: Automated MLP for Sequential Recommendationscited by 25
  2. 2024Can Small Language Models be Good Reasoners for Sequential Recommendation?cited by 25
  3. 2022Trustworthy Recommender Systemscited by 21
  4. 2022PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-term User Engagementcited by 21
  5. 2022Multi-Behavior Sequential Recommendation with Temporal Graph Transformercited by 20
  6. 2022Enhancing Sequential Recommendation with Graph Contrastive Learningcited by 18
  7. 2024Language Representations Can be What Recommenders Need: Findings and Potentialscited by 18
  8. 2021Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate Predictioncited by 17
  9. 2024Image Fusion for Cross-Domain Sequential Recommendationcited by 17
  10. 2025A Survey of Foundation Model-Powered Recommender Systems: From Feature-Based, Generative to Agentic Paradigmscited by 17
  11. 2023Mixed Attention Network for Cross-domain Sequential Recommendationcited by 15
  12. 2025Hierarchical Time-Aware Mixture of Experts for Multi-Modal Sequential Recommendationcited by 14
  13. 2022Counterfactual inference in sequential experimentscited by 13
  14. 2024Training Machine Learning models at the Edge: A Surveycited by 11
  15. 2024Knowledge Graph Enhanced Language Agents for Recommendationcited by 11
  16. 2025LLM-Enhanced Multimodal Fusion for Cross-Domain Sequential Recommendationcited by 11
  17. 2025HiD-VAE: Interpretable Generative Recommendation via Hierarchical and Disentangled Semantic IDscited by 11
  18. 2022ResAct: Reinforcing Long-term Engagement in Sequential Recommendation with Residual Actorcited by 10
  19. 2022POIBERT: A Transformer-based Model for the Tour Recommendation Problemcited by 10
  20. 2024LLM4DSR: Leveraging Large Language Model for Denoising Sequential Recommendationcited by 10
  21. 2024SIGMA: Selective Gated Mamba for Sequential Recommendationcited by 10
  22. 2022Sequential/Session-based Recommendations: Challenges, Approaches, Applications and Opportunitiescited by 9
  23. 2025LLM-based User Profile Management for Recommender Systemcited by 9
  24. 2021Fast Variational AutoEncoder with Inverted Multi-Index for Collaborative Filteringcited by 8
  25. 2022Accurate Action Recommendation for Smart Home via Two-Level Encoders and Commonsense Knowledgecited by 8
  26. 2023Enabling Resource-efficient AIoT System with Cross-level Optimization: A surveycited by 8
  27. 2024Preference Diffusion for Recommendationcited by 8
  28. 2024InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Predictioncited by 8
  29. 2021Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E-Commercecited by 7
  30. 2023A Scalable Framework for Automatic Playlist Continuation on Music Streaming Servicescited by 7
  31. 2023Masked and Swapped Sequence Modeling for Next Novel Basket Recommendation in Grocery Shoppingcited by 7
  32. 2023Learning from Negative User Feedback and Measuring Responsiveness for Sequential Recommenderscited by 7
  33. 2024Molar: Multimodal LLMs with Collaborative Filtering Alignment for Enhanced Sequential Recommendationcited by 7
  34. 2025GRAM: Generative Recommendation via Semantic-aware Multi-granular Late Fusioncited by 7
  35. 2023Optimizing Long-term Value for Auction-Based Recommender Systems via On-Policy Reinforcement Learningcited by 6
  36. 2023RecFusion: A Binomial Diffusion Process for 1D Data for Recommendationcited by 6
  37. 2024Modeling Temporal Positive and Negative Excitation for Sequential Recommendationcited by 6
  38. 2024Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendationcited by 6

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