mlsanityData to 14 Oct 2026

Bridge the Domains: Large Language Models Enhanced Cross-domain Sequential Recommendation

arXiv 2504.18383 ↗First posted 25 Apr 2025cs.IR cs.AIcited by 15

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Abstract (arXiv)

Cross-domain Sequential Recommendation (CDSR) aims to extract the preference from the user's historical interactions across various domains. Despite some progress in CDSR, two problems set the barrier for further advancements, i.e., overlap dilemma and transition complexity. The former means existing CDSR methods severely rely on users who own interactions on all domains to learn cross-domain item relationships, compromising the practicability. The latter refers to the difficulties in learning the complex transition patterns from the mixed behavior sequences. With powerful representation and reasoning abilities, Large Language Models (LLMs) are promising to address these two problems by bridging the items and capturing the user's preferences from a semantic view. Therefore, we propose an LLMs Enhanced Cross-domain Sequential Recommendation model (LLM4CDSR). To obtain the semantic item relationships, we first propose an LLM-based unified representation module to represent items. Then, a trainable adapter with contrastive regularization is designed to adapt the CDSR task. Besides, a hierarchical LLMs profiling module is designed to summarize user cross-domain preferences. Finally, these two modules are integrated into the proposed tri-thread framework to derive recommendations. We have conducted extensive experiments on three public cross-domain datasets, validating the effectiveness of LLM4CDSR. We have released the code online.

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). Builds on 39 of its 59 references that are in the map. First posted on arXiv 25 Apr 2025.

Builds on

39 of 59 references.

References · 39

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  4. 2018Self-Attentive Sequential Recommendationcited by 1,184
  5. 2019BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformercited by 964
  6. 2015Session-based Recommendations with Recurrent Neural Networkscited by 695
  7. 2020Graph Neural Networks in Recommender Systems: A Surveycited by 494
  8. 2023A Survey on Large Language Models for Recommendationcited by 379
  9. 2023TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendationcited by 337
  10. 2023Representation Learning with Large Language Models for Recommendationcited by 155
  11. 2023How Can Recommender Systems Benefit from Large Language Models: A Surveycited by 142
  12. 2021Contrastive Learning for Representation Degeneration Problem in Sequential Recommendationcited by 121
27 more
  1. 2023When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applicationscited by 111
  2. 2018Deep Reinforcement Learning for Page-wise Recommendationscited by 100
  3. 2020Controllable Multi-Interest Framework for Recommendationcited by 93
  4. 2018Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learningcited by 71
  5. 2024On Softmax Direct Preference Optimization for Recommendationcited by 64
  6. 2021A Survey of Machine Learning for Computer Architecture and Systemscited by 53
  7. 2024LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendationcited by 47
  8. 2023Diffusion Augmentation for Sequential Recommendationcited by 38
  9. 2023Multimodal Recommender Systems: A Surveycited by 37
  10. 2023Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priorscited by 34
  11. 2024M3oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Frameworkcited by 32
  12. 2023Contrastive Cross-Domain Sequential Recommendationcited by 31
  13. 2021A Survey on Cross-domain Recommendation: Taxonomies, Methods, and Future Directionscited by 30
  14. 2023Multi-Task Deep Recommender Systems: A Surveycited by 30
  15. 2023Multi-Task Recommendations with Reinforcement Learningcited by 26
  16. 2024Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviorscited by 23
  17. 2023HAMUR: Hyper Adapter for Multi-Domain Recommendationcited by 21
  18. 2023Embedding in Recommender Systems: A Surveycited by 20
  19. 2023Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptionscited by 20
  20. 2023Triple Sequence Learning for Cross-domain Recommendationcited by 19
  21. 2024Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential Recommendationcited by 19
  22. 2024LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendationcited by 19
  23. 2024LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential Recommendationcited by 18
  24. 2024A Survey on Cross-Domain Sequential Recommendationcited by 16
  25. 2024Pacer and Runner: Cooperative Learning Framework between Single- and Cross-Domain Sequential Recommendationcited by 13
  26. 2024GOT4Rec: Graph of Thoughts for Sequential Recommendationcited by 5
  27. 2023Unbiased and Robust: External Attention-enhanced Graph Contrastive Learning for Cross-domain Sequential Recommendationcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 7; 2026: 8.

15 papers.

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  1. 2025R2ec: Towards Large Recommender Models with Reasoningcited by 13
  2. 2025QualBench: Benchmarking Chinese LLMs with Localized Professional Qualifications for Vertical Domain Evaluationcited by 5
  3. 2025GFlowGR: Fine-tuning Generative Recommendation Frameworks with Generative Flow Networkscited by 3
  4. 2025A Comprehensive Review on Harnessing Large Language Models to Overcome Recommender System Challengescited by 3
  5. 2025Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDscited by 2
  6. 2025LLM-EDT: Large Language Model Enhanced Cross-domain Sequential Recommendation with Dual-phase Trainingcited by 1
  7. 2026Sharpness-aware Model Merging with Salience Recovery for LLM-based Cross-Domain Sequential Recommendationcited by 1
  8. 2025Cross-attention Secretly Performs Orthogonal Alignment in Recommendation Modelscited by 0
  9. 2026MergeRec: Model Merging for Data-Isolated Cross-Domain Sequential Recommendationcited by 0
  10. 2026Fusion and Alignment Enhancement with Large Language Models for Tail-item Sequential Recommendationcited by 0
  11. 2026Breaking the Information Silo: Semantic Personas for Cross-Domain Recommendationcited by 0
  12. 2026Empowering Cross-Domain Sequential Recommendation with Hybrid Tokenization and Serial-Parallel Decodingcited by 0
3 more
  1. 2026CoRCi: Cross-Reconstruction of Coherent Interests Modeling in Cross-Domain Sequential Recommendationcited by 0
  2. 2026Tlow: Flow-based Item Tokenizer for Recommendationcited by 0
  3. 2026P3Rec: Distilling Prior--Posterior Preference Reasoning for LLM-based Recommendationcited by 0

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  1. 2024Cross-Domain Recommendation Meets Large Language Models ↗
  2. 2026From Clues to Generation: Language-Guided Conditional Diffusion for Cross-Domain Recommendation
  3. 2025Align-for-Fusion: Harmonizing Triple Preferences via Dual-oriented Diffusion for Cross-domain Sequential Recommendation
  4. 2024Unleash LLMs Potential for Sequential Recommendation by Coordinating Dual Dynamic Index Mechanism
  5. 2025Beyond Negative Transfer: Disentangled Preference-Guided Diffusion for Cross-Domain Sequential Recommendation
  6. 2024CALRec: Contrastive Alignment of Generative LLMs for Sequential Recommendation
  7. 2025Bidirectional Knowledge Distillation for Enhancing Sequential Recommendation with Large Language Models
  8. 2025Exploring Preference-Guided Diffusion Model for Cross-Domain Recommendation