mlsanityData to 14 Oct 2026

Conversational Recommender System

arXiv 1806.03277 ↗First posted 8 Jun 2018cs.IRcited by 115

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Abstract (arXiv)

A personalized conversational sales agent could have much commercial potential. E-commerce companies such as Amazon, eBay, JD, Alibaba etc. are piloting such kind of agents with their users. However, the research on this topic is very limited and existing solutions are either based on single round adhoc search engine or traditional multi round dialog system. They usually only utilize user inputs in the current session, ignoring users' long term preferences. On the other hand, it is well known that sales conversion rate can be greatly improved based on recommender systems, which learn user preferences based on past purchasing behavior and optimize business oriented metrics such as conversion rate or expected revenue. In this work, we propose to integrate research in dialog systems and recommender systems into a novel and unified deep reinforcement learning framework to build a personalized conversational recommendation agent that optimizes a per session based utility function.

Key facts. Cited by 115 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Jun 2018.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 19; 2022: 22; 2023: 24; 2024: 21; 2025: 19; 2026: 10.

115 papers.

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  1. 2022Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)cited by 402
  2. 2023How Can Recommender Systems Benefit from Large Language Models: A Surveycited by 142
  3. 2023User Behavior Simulation with Large Language Model based Agentscited by 140
  4. 2021Advances and Challenges in Conversational Recommender Systems: A Surveycited by 118
  5. 2023When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunitiescited by 90
  6. 2022Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learningcited by 86
  7. 2023Large Language Models for Generative Recommendation: A Survey and Visionary Discussionscited by 73
  8. 2023Leveraging Large Language Models in Conversational Recommender Systemscited by 63
  9. 2024Evaluating Large Language Models as Generative User Simulators for Conversational Recommendationcited by 48
  10. 2021RevCore: Review-augmented Conversational Recommendationcited by 47
  11. 2021DuRecDial 2.0: A Bilingual Parallel Corpus for Conversational Recommendationcited by 46
  12. 2021Learning to Ask Appropriate Questions in Conversational Recommendationcited by 35
38 more
  1. 2021CRSLab: An Open-Source Toolkit for Building Conversational Recommender Systemcited by 34
  2. 2024Stereotype or Personalization? User Identity Biases Chatbot Recommendationscited by 34
  3. 2022A Unified Multi-task Learning Framework for Multi-goal Conversational Recommender Systemscited by 32
  4. 2022User-Centric Conversational Recommendation with Multi-Aspect User Modelingcited by 29
  5. 2024How Reliable is Your Simulator? Analysis on the Limitations of Current LLM-based User Simulators for Conversational Recommendationcited by 27
  6. 2023Multi-Task Recommendations with Reinforcement Learningcited by 26
  7. 2022Evaluating Mixed-initiative Conversational Search Systems via User Simulationcited by 25
  8. 2022C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender Systemcited by 24
  9. 2025iAgent: LLM Agent as a Shield between User and Recommender Systemscited by 23
  10. 2021Learning Neural Templates for Recommender Dialogue Systemcited by 22
  11. 2022Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendationcited by 22
  12. 2022BARCOR: Towards A Unified Framework for Conversational Recommendation Systemscited by 21
  13. 2024Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Trackingcited by 18
  14. 2025Are Generative AI Agents Effective Personalized Financial Advisors?cited by 18
  15. 2025A Survey of Foundation Model-Powered Recommender Systems: From Feature-Based, Generative to Agentic Paradigmscited by 17
  16. 2023TREA: Tree-Structure Reasoning Schema for Conversational Recommendationcited by 15
  17. 2021KECRS: Towards Knowledge-Enriched Conversational Recommendation Systemcited by 14
  18. 2021RecInDial: A Unified Framework for Conversational Recommendation with Pretrained Language Modelscited by 14
  19. 2024Zero-shot Persuasive Chatbots with LLM-Generated Strategies and Information Retrievalcited by 14
  20. 2023Sparks of Artificial General Recommender (AGR): Early Experiments with ChatGPTcited by 13
  21. 2024A LLM-based Controllable, Scalable, Human-Involved User Simulator Framework for Conversational Recommender Systemscited by 13
  22. 2022Comparison-based Conversational Recommender System with Relative Bandit Feedbackcited by 12
  23. 2023Efficient Explorative Key-term Selection Strategies for Conversational Contextual Banditscited by 12
  24. 2024Exploring the Impact of Large Language Models on Recommender Systems: An Extensive Reviewcited by 12
  25. 2025RecUserSim: A Realistic and Diverse User Simulator for Evaluating Conversational Recommender Systemscited by 12
  26. 2021Wizard of Search Engine: Access to Information Through Conversations with Search Enginescited by 11
  27. 2023Improving Conversational Recommendation Systems via Bias Analysis and Language-Model-Enhanced Data Augmentationcited by 11
  28. 2024Behavior Alignment: A New Perspective of Evaluating LLM-based Conversational Recommender Systemscited by 11
  29. 2021Generating Usage-related Questions for Preference Elicitation in Conversational Recommender Systemscited by 10
  30. 2022Bundle MCR: Towards Conversational Bundle Recommendationcited by 10
  31. 2022Hierarchical Conversational Preference Elicitation with Bandit Feedbackcited by 10
  32. 2023Talk the Walk: Synthetic Data Generation for Conversational Music Recommendationcited by 10
  33. 2022Metaphorical User Simulators for Evaluating Task-oriented Dialogue Systemscited by 9
  34. 2023AGI for Agriculturecited by 9
  35. 2024Parameter-Efficient Conversational Recommender System as a Language Processing Taskcited by 9
  36. 2024Concept -- An Evaluation Protocol on Conversational Recommender Systems with System-centric and User-centric Factorscited by 9
  37. 2021Recommender systems based on graph embedding techniques: A comprehensive reviewcited by 8
  38. 2022Knowledge Management System with NLP-Assisted Annotations: A Brief Survey and Outlookcited by 7

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