mlsanityData to 7 Oct 2026

KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems

arXiv 2202.10842 ↗First posted 22 Feb 2022cs.IR cs.HCcited by 94

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Abstract (arXiv)

The progress of recommender systems is hampered mainly by evaluation as it requires real-time interactions between humans and systems, which is too laborious and expensive. This issue is usually approached by utilizing the interaction history to conduct offline evaluation. However, existing datasets of user-item interactions are partially observed, leaving it unclear how and to what extent the missing interactions will influence the evaluation. To answer this question, we collect a fully-observed dataset from Kuaishou's online environment, where almost all 1,411 users have been exposed to all 3,327 items. To the best of our knowledge, this is the first real-world fully-observed data with millions of user-item interactions. With this unique dataset, we conduct a preliminary analysis of how the two factors - data density and exposure bias - affect the evaluation results of multi-round conversational recommendation. Our main discoveries are that the performance ranking of different methods varies with the two factors, and this effect can only be alleviated in certain cases by estimating missing interactions for user simulation. This demonstrates the necessity of the fully-observed dataset. We release the dataset and the pipeline implementation for evaluation at https://kuairec.com

Key facts. Cited by 94 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Feb 2022.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 11; 2024: 19; 2025: 27; 2026: 37.

94 papers.

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  1. 2023Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusioncited by 72
  2. 2023Binary Classification with Confidence Differencecited by 13
  3. 2024Generative Regression Based Watch Time Prediction for Short-Video Recommendationcited by 13
  4. 2023Scalable Neural Contextual Bandit for Recommender Systemscited by 12
  5. 2024From Variability to Stability: Advancing RecSys Benchmarking Practicescited by 12
  6. 2024Relevance meets Diversity: A User-Centric Framework for Knowledge Exploration through Recommendationscited by 11
  7. 2023HyperBandit: Contextual Bandit with Hypernewtork for Time-Varying User Preferences in Streaming Recommendationcited by 10
  8. 2024EasyRL4Rec: An Easy-to-use Library for Reinforcement Learning Based Recommender Systemscited by 8
  9. 2024Debiased Recommendation with Noisy Feedbackcited by 8
  10. 2024Effective Off-Policy Evaluation and Learning in Contextual Combinatorial Banditscited by 8
  11. 2024Doubly Calibrated Estimator for Recommendation on Data Missing Not At Randomcited by 7
  12. 2024Policy Learning for Balancing Short-Term and Long-Term Rewardscited by 7
38 more
  1. 2025MUSE: A Simple Yet Effective Multimodal Search-Based Framework for Lifelong User Interest Modelingcited by 6
  2. 2026Towards Real-world Human Behavior Simulation: Benchmarking Large Language Models on Long-horizon, Cross-scenario, Heterogeneous Behavior Tracescited by 6
  3. 2024Bayesian Off-Policy Evaluation and Learning for Large Action Spacescited by 5
  4. 2024Cache-Aware Reinforcement Learning in Large-Scale Recommender Systemscited by 5
  5. 2025KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendationcited by 5
  6. 2024ROLeR: Effective Reward Shaping in Offline Reinforcement Learning for Recommender Systemscited by 4
  7. 2025Qilin: A Multimodal Information Retrieval Dataset with APP-level User Sessionscited by 4
  8. 2025Addressing Missing Data Issue for Diffusion-based Recommendationcited by 4
  9. 2025Martingale Posterior Neural Networks for Fast Sequential Decision Makingcited by 4
  10. 2023Uncertainty-Aware Instance Reweighting for Off-Policy Learningcited by 3
  11. 2025Diffusion Models in Recommendation Systems: A Surveycited by 3
  12. 2025GFlowGR: Fine-tuning Generative Recommendation Frameworks with Generative Flow Networkscited by 3
  13. 2025CTR-Sink: Attention Sink for Language Models in Click-Through Rate Predictioncited by 3
  14. 2026HiSAC: Hierarchical Sparse Activation Compression for Ultra-long Sequence Modeling in Recommenderscited by 3
  15. 2026GISTBench: Evaluating LLM User Understanding via Evidence-Based Interest Verificationcited by 3
  16. 2026PACEvolve++: Improving Test-time Learning for Evolutionary Search Agentscited by 3
  17. 2026RecHarness: A Bandit-Routed Agentic Harness for Self-Evolving Recommender Systemscited by 3
  18. 2024Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interferencecited by 2
  19. 2024Calibrating the Predictions for Top-N Recommendationscited by 2
  20. 2025Policy Design for Two-sided Platforms with Participation Dynamicscited by 2
  21. 2025Policy-Guided Causal State Representation for Offline Reinforcement Learning Recommendationcited by 2
  22. 2025DARLR: Dual-Agent Offline Reinforcement Learning for Recommender Systems with Dynamic Rewardcited by 2
  23. 2025Mirroring Users: Towards Building Preference-aligned User Simulator with User Feedback in Recommendationcited by 2
  24. 2025RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendationcited by 2
  25. 2025On Efficiency-Effectiveness Trade-off of Diffusion-based Recommenderscited by 2
  26. 2025Tree of Preferences for Diversified Recommendationcited by 2
  27. 2026UniMoMo: Expert Merging-Based MoE Acceleration for Large Recommendation Modelscited by 2
  28. 2023Graph-Based Model-Agnostic Data Subsampling for Recommendation Systemscited by 1
  29. 2023Non-Stationary Contextual Bandit Learning via Neural Predictive Ensemble Samplingcited by 1
  30. 2023Causal Structure Representation Learning of Confounders in Latent Space for Recommendationcited by 1
  31. 2024RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systemscited by 1
  32. 2024The Importance of Causality in Decision Making: A Perspective on Recommender Systemscited by 1
  33. 2025Revisiting Clustering of Neural Bandits: Selective Reinitialization for Mitigating Loss of Plasticitycited by 1
  34. 2025A General Framework for Off-Policy Learning with Partially-Observed Rewardcited by 1
  35. 2025Energy-Guided Diffusion Sampling for Long-Term User Behavior Prediction in Reinforcement Learning-based Recommendationcited by 1
  36. 2025HiGR: Industrial-Scale Hierarchical Generative Slate Recommendation Framework in Tencentcited by 1
  37. 2026LLM-Enhanced Reinforcement Learning for Long-Term User Satisfaction in Interactive Recommendationcited by 1
  38. 2026Enhancing Bandit Algorithms with LLMs for Time-varying User Preferences in Streaming Recommendationscited by 1

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