mlsanityData to 14 Oct 2026

Session-based Recommendations with Recurrent Neural Networks

arXiv 1511.06939 ↗First posted 21 Nov 2015cs.LG cs.IR cs.NEcited by 695

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Cited by 43 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We apply recurrent neural networks (RNN) on a new domain, namely recommender systems. Real-life recommender systems often face the problem of having to base recommendations only on short session-based data (e.g. a small sportsware website) instead of long user histories (as in the case of Netflix). In this situation the frequently praised matrix factorization approaches are not accurate. This problem is usually overcome in practice by resorting to item-to-item recommendations, i.e. recommending similar items. We argue that by modeling the whole session, more accurate recommendations can be provided. We therefore propose an RNN-based approach for session-based recommendations. Our approach also considers practical aspects of the task and introduces several modifications to classic RNNs such as a ranking loss function that make it more viable for this specific problem. Experimental results on two data-sets show marked improvements over widely used approaches.

Key facts. Cited by 695 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Nov 2015.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 52; 2022: 60; 2023: 115; 2024: 152; 2025: 154; 2026: 162.

695 papers.

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  1. 2023Large Language Models are Zero-Shot Rankers for Recommender Systemscited by 309
  2. 2023Recommender Systems with Generative Retrievalcited by 198
  3. 2023Recommender Systems in the Era of Large Language Models (LLMs)cited by 189
  4. 2024Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendationscited by 188
  5. 2023Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approachcited by 168
  6. 2023RecMind: Large Language Model Powered Agent For Recommendationcited by 129
  7. 2023Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Predictioncited by 116
  8. 2022Filter-enhanced MLP is All You Need for Sequential Recommendationcited by 96
  9. 2023DiffuRec: A Diffusion Model for Sequential Recommendationcited by 93
  10. 2023When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunitiescited by 90
  11. 2023ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendationcited by 77
  12. 2023Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusioncited by 74
38 more
  1. 2024On Softmax Direct Preference Optimization for Recommendationcited by 64
  2. 2024HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modelingcited by 63
  3. 2021A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendationcited by 59
  4. 2024A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)cited by 58
  5. 2021Contrastive Self-supervised Sequential Recommendation with Robust Augmentationcited by 56
  6. 2023Zero-Shot Next-Item Recommendation using Large Pretrained Language Modelscited by 53
  7. 2024IDGenRec: LLM-RecSys Alignment with Textual ID Learningcited by 53
  8. 2025Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendationcited by 51
  9. 2024Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender Systemcited by 50
  10. 2024LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendationcited by 47
  11. 2021End-to-End User Behavior Retrieval in Click-Through RatePrediction Modelcited by 45
  12. 2025Agentic Web: Weaving the Next Web with AI Agentscited by 45
  13. 2023Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generationcited by 42
  14. 2023E4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential Recommendationcited by 39
  15. 2021Sparse-Interest Network for Sequential Recommendationcited by 38
  16. 2023UP5: Unbiased Foundation Model for Fairness-aware Recommendationcited by 38
  17. 2023Diffusion Augmentation for Sequential Recommendationcited by 38
  18. 2021Black-Box Attacks on Sequential Recommenders via Data-Free Model Extractioncited by 37
  19. 2024Plug-in Diffusion Model for Sequential Recommendationcited by 37
  20. 2023TransAct: Transformer-based Realtime User Action Model for Recommendation at Pinterestcited by 35
  21. 2025Sparse Meets Dense: Unified Generative Recommendations with Cascaded Sparse-Dense Representationscited by 35
  22. 2021CRSLab: An Open-Source Toolkit for Building Conversational Recommender Systemcited by 34
  23. 2024Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendationcited by 33
  24. 2024Customizing Language Models with Instance-wise LoRA for Sequential Recommendationcited by 32
  25. 2023MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendationcited by 31
  26. 2023LLMRec: Benchmarking Large Language Models on Recommendation Taskcited by 30
  27. 2023Turning Dross Into Gold Loss: is BERT4Rec really better than SASRec?cited by 30
  28. 2023Large Language Models for Intent-Driven Session Recommendationscited by 30
  29. 2025PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendationscited by 30
  30. 2023gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Samplingcited by 29
  31. 2023An Attentive Inductive Bias for Sequential Recommendation beyond the Self-Attentioncited by 28
  32. 2024Rethinking Large Language Model Architectures for Sequential Recommendationscited by 27
  33. 2023A Survey on User Behavior Modeling in Recommender Systemscited by 26
  34. 2024Can Small Language Models be Good Reasoners for Sequential Recommendation?cited by 26
  35. 2024IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFTcited by 26
  36. 2023Intelligent Model Update Strategy for Sequential Recommendationcited by 25
  37. 2023AutoMLP: Automated MLP for Sequential Recommendationscited by 25
  38. 2023A Diffusion model for POI recommendationcited by 24

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