mlsanityData to 7 Oct 2026

RecBole 2.0: Towards a More Up-to-Date Recommendation Library

arXiv 2206.07351 ↗First posted 15 Jun 2022cs.IRcited by 39

Not on the map. Why?

Abstract (arXiv)

In order to support the study of recent advances in recommender systems, this paper presents an extended recommendation library consisting of eight packages for up-to-date topics and architectures. First of all, from a data perspective, we consider three important topics related to data issues (i.e., sparsity, bias and distribution shift), and develop five packages accordingly: meta-learning, data augmentation, debiasing, fairness and cross-domain recommendation. Furthermore, from a model perspective, we develop two benchmarking packages for Transformer-based and graph neural network (GNN)-based models, respectively. All the packages (consisting of 65 new models) are developed based on a popular recommendation framework RecBole, ensuring that both the implementation and interface are unified. For each package, we provide complete implementations from data loading, experimental setup, evaluation and algorithm implementation. This library provides a valuable resource to facilitate the up-to-date research in recommender systems. The project is released at the link: https://github.com/RUCAIBox/RecBole2.0.

Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Jun 2022.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 6; 2024: 17; 2025: 10; 2026: 3.

39 papers.

Sort:

By area:

  1. 2023Large Language Models are Zero-Shot Rankers for Recommender Systemscited by 307
  2. 2023Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approachcited by 168
  3. 2022Learning Vector-Quantized Item Representation for Transferable Sequential Recommenderscited by 112
  4. 2022A Comprehensive Survey on Trustworthy Recommender Systemscited by 32
  5. 2022Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendationcited by 16
  6. 2024Pacer and Runner: Cooperative Learning Framework between Single- and Cross-Domain Sequential Recommendationcited by 13
  7. 2025TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendationcited by 13
  8. 2024From Variability to Stability: Advancing RecSys Benchmarking Practicescited by 12
  9. 2023APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendationcited by 10
  10. 2024RecGPT: Generative Personalized Prompts for Sequential Recommendation via ChatGPT Training Paradigmcited by 8
  11. 2024RevGNN: Negative Sampling Enhanced Contrastive Graph Learning for Academic Reviewer Recommendationcited by 8
  12. 2023Cracking the Code of Negative Transfer: A Cooperative Game Theoretic Approach for Cross-Domain Sequential Recommendationcited by 7
27 more
  1. 2024How Does Message Passing Improve Collaborative Filtering?cited by 5
  2. 2024Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Methodcited by 5
  3. 2024How Fair is Your Diffusion Recommender Model?cited by 5
  4. 2024EulerFormer: Sequential User Behavior Modeling with Complex Vector Attentioncited by 3
  5. 2024RePlay: a Recommendation Framework for Experimentation and Production Usecited by 3
  6. 2024Temporal Linear Item-Item Model for Sequential Recommendationcited by 3
  7. 2025Efficient and Responsible Adaptation of Large Language Models for Robust and Equitable Top-k Recommendationscited by 2
  8. 2025Do We Really Need Specialization? Evaluating Generalist Text Embeddings for Zero-Shot Recommendation and Searchcited by 2
  9. 2025Sequential Data Augmentation for Generative Recommendationcited by 2
  10. 2023Causal Structure Representation Learning of Confounders in Latent Space for Recommendationcited by 1
  11. 2024GACE: Learning Graph-Based Cross-Page Ads Embedding For Click-Through Rate Predictioncited by 1
  12. 2024RecWizard: A Toolkit for Conversational Recommendation with Modular, Portable Models and Interactive User Interfacecited by 1
  13. 2024KG4RecEval: Does Knowledge Graph Really Matter for Recommender Systems?cited by 1
  14. 2024Hyperbolic Knowledge Transfer in Cross-Domain Recommendation Systemcited by 1
  15. 2024Fair Augmentation for Graph Collaborative Filteringcited by 1
  16. 2024MDAP: A Multi-view Disentangled and Adaptive Preference Learning Framework for Cross-Domain Recommendationcited by 1
  17. 2025LightKG: Efficient Knowledge-Aware Recommendations with Simplified GNN Architecturecited by 1
  18. 2025Rethinking Popularity Bias in Collaborative Filtering via Analytical Vector Decompositioncited by 1
  19. 2023Is Meta-Learning the Right Approach for the Cold-Start Problem in Recommender Systems?cited by 0
  20. 2024Against Filter Bubbles: Diversified Music Recommendation via Weighted Hypergraph Embedding Learningcited by 0
  21. 2025Enhancing Recommender Systems Using Textual Embeddings from Pre-trained Language Modelscited by 0
  22. 2025INTERPOS: Interaction Rhythm Guided Positional Morphing for Mobile App Recommender Systemscited by 0
  23. 2025Modeling User Preferences as Distributions for Optimal Transport-Based Cross-Domain Recommendation under Non-Overlapping Settingscited by 0
  24. 2025A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directionscited by 0
  25. 2026The Diversity Paradox revisited: Systemic Effects of Feedback Loops in Recommender Systemscited by 0
  26. 2026HORIZON: A Benchmark for In-the-wild User Behaviour Modelingcited by 0
  27. 2026FineSID: Scalable and Efficient Semantic Identifier Learning for Generative Recommendationcited by 0