mlsanityData to 14 Oct 2026

Deep Reinforcement Learning for Page-wise Recommendations

arXiv 1805.02343 ↗First posted 7 May 2018cs.IRcited by 100

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Abstract (arXiv)

Recommender systems can mitigate the information overload problem by suggesting users' personalized items. In real-world recommendations such as e-commerce, a typical interaction between the system and its users is -- users are recommended a page of items and provide feedback; and then the system recommends a new page of items. To effectively capture such interaction for recommendations, we need to solve two key problems -- (1) how to update recommending strategy according to user's textitreal-time feedback, and 2) how to generate a page of items with proper display, which pose tremendous challenges to traditional recommender systems. In this paper, we study the problem of page-wise recommendations aiming to address aforementioned two challenges simultaneously. In particular, we propose a principled approach to jointly generate a set of complementary items and the corresponding strategy to display them in a 2-D page; and propose a novel page-wise recommendation framework based on deep reinforcement learning, DeepPage, which can optimize a page of items with proper display based on real-time feedback from users. The experimental results based on a real-world e-commerce dataset demonstrate the effectiveness of the proposed framework.

Key facts. Cited by 100 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 May 2018.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 24; 2022: 14; 2023: 15; 2024: 17; 2025: 23; 2026: 7.

100 papers.

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  1. 2024Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendationscited by 188
  2. 2025Process vs. Outcome Reward: Which is Better for Agentic RAG Reinforcement Learningcited by 70
  3. 2021A Provably Efficient Algorithm for Linear Markov Decision Process with Low Switching Costcited by 40
  4. 2022A Comprehensive Survey on Trustworthy Recommender Systemscited by 32
  5. 2021AutoLoss: Automated Loss Function Search in Recommendationscited by 31
  6. 2021Provably Efficient Black-Box Action Poisoning Attacks Against Reinforcement Learningcited by 29
  7. 2025A Survey of Personalization: From RAG to Agentcited by 27
  8. 2021Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environmentscited by 26
  9. 2023Multi-Task Recommendations with Reinforcement Learningcited by 26
  10. 2024Large Language Models are Learnable Planners for Long-Term Recommendationcited by 24
  11. 2021User Tampering in Reinforcement Learning Recommender Systemscited by 23
  12. 2022Multi-Task Fusion via Reinforcement Learning for Long-Term User Satisfaction in Recommender Systemscited by 22
38 more
  1. 2021Reinforced Imitative Graph Representation Learning for Mobile User Profiling: An Adversarial Training Perspectivecited by 21
  2. 2021RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystemscited by 21
  3. 2021A Survey of Deep Reinforcement Learning in Recommender Systems: A Systematic Review and Future Directionscited by 21
  4. 2022Understanding the Limits of Poisoning Attacks in Episodic Reinforcement Learningcited by 21
  5. 2023A General Offline Reinforcement Learning Framework for Interactive Recommendationcited by 18
  6. 2023Agent4Ranking: Semantic Robust Ranking via Personalized Query Rewriting Using Multi-agent LLMcited by 18
  7. 2021Accelerating Offline Reinforcement Learning Application in Real-Time Bidding and Recommendation: Potential Use of Simulationcited by 16
  8. 2021Variational Quantum Soft Actor-Criticcited by 15
  9. 2025Bridge the Domains: Large Language Models Enhanced Cross-domain Sequential Recommendationcited by 15
  10. 2021Blockchain-based Recommender Systems: Applications, Challenges and Future Opportunitiescited by 11
  11. 2023Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learningcited by 11
  12. 2025Personalize Before Retrieve: LLM-based Personalized Query Expansion for User-Centric Retrievalcited by 11
  13. 2023On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systemscited by 10
  14. 2021Model-free Policy Learning with Reward Gradientscited by 9
  15. 2021Reinforcement Learning to Optimize Lifetime Value in Cold-Start Recommendationcited by 9
  16. 2022Local Policy Improvement for Recommender Systemscited by 9
  17. 2023Multi-agent Attacks for Black-box Social Recommendationscited by 9
  18. 2024EasyRL4Rec: An Easy-to-use Library for Reinforcement Learning Based Recommender Systemscited by 9
  19. 2022Modeling Users' Contextualized Page-wise Feedback for Click-Through Rate Prediction in E-commerce Searchcited by 8
  20. 2022Probabilistic Rank and Reward: A Scalable Model for Slate Recommendationcited by 8
  21. 2023Optimizing Audio Recommendations for the Long-Term: A Reinforcement Learning Perspectivecited by 8
  22. 2022Reward Shaping for User Satisfaction in a REINFORCE Recommendercited by 6
  23. 2021MARL with General Utilities via Decentralized Shadow Reward Actor-Criticcited by 5
  24. 2021Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendationcited by 4
  25. 2021Value Penalized Q-Learning for Recommender Systemscited by 4
  26. 2024DNS-Rec: Data-aware Neural Architecture Search for Recommender Systemscited by 4
  27. 2024Evolutionary Reinforcement Learning: A Systematic Review and Future Directionscited by 4
  28. 2024ROLeR: Effective Reward Shaping in Offline Reinforcement Learning for Recommender Systemscited by 4
  29. 2024Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language Modelscited by 4
  30. 2025SampleLLM: Optimizing Tabular Data Synthesis in Recommendationscited by 4
  31. 2026Exploring Recommender System Evaluation: A Multi-Modal User Agent Framework for A/B Testingcited by 4
  32. 2022BCRLSP: An Offline Reinforcement Learning Framework for Sequential Targeted Promotioncited by 3
  33. 2024Retentive Decision Transformer with Adaptive Masking for Reinforcement Learning based Recommendation Systemscited by 3
  34. 2024Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policiescited by 3
  35. 2024Mitigating Suboptimality of Deterministic Policy Gradients in Complex Q-functionscited by 3
  36. 2024An Investigation of Offline Reinforcement Learning in Factorisable Action Spacescited by 3
  37. 2025Time-Constrained Recommendations: Reinforcement Learning Strategies for E-Commercecited by 3
  38. 2026AgentOS: From Application Silos to a Natural Language-Driven Data Ecosystemcited by 3

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