mlsanityData to 13 Oct 2026

Towards Knowledge-Based Recommender Dialog System

arXiv 1908.05391 ↗First posted 15 Aug 2019cs.CL cs.IR cs.LGcited by 112

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Abstract (arXiv)

In this paper, we propose a novel end-to-end framework called KBRD, which stands for Knowledge-Based Recommender Dialog System. It integrates the recommender system and the dialog generation system. The dialog system can enhance the performance of the recommendation system by introducing knowledge-grounded information about users' preferences, and the recommender system can improve that of the dialog generation system by providing recommendation-aware vocabulary bias. Experimental results demonstrate that our proposed model has significant advantages over the baselines in both the evaluation of dialog generation and recommendation. A series of analyses show that the two systems can bring mutual benefits to each other, and the introduced knowledge contributes to both their performances.

Key facts. Cited by 112 papers in the map (data through 13 Oct 2026). First posted on arXiv 15 Aug 2019.

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Citing papers per year: 2021: 18; 2022: 22; 2023: 28; 2024: 20; 2025: 14; 2026: 10.

112 papers.

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  1. 2023Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approachcited by 168
  2. 2023Recommender AI Agent: Integrating Large Language Models for Interactive Recommendationscited by 130
  3. 2023Large Language Models as Zero-Shot Conversational Recommenderscited by 126
  4. 2021Advances and Challenges in Conversational Recommender Systems: A Surveycited by 118
  5. 2022Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learningcited by 85
  6. 2023Leveraging Large Language Models in Conversational Recommender Systemscited by 63
  7. 2024A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)cited by 58
  8. 2021Incorporating Domain Knowledge into Deep Neural Networkscited by 56
  9. 2023Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Modelscited by 48
  10. 2021RevCore: Review-augmented Conversational Recommendationcited by 47
  11. 2021Learning to Ask Appropriate Questions in Conversational Recommendationcited by 35
  12. 2021CRSLab: An Open-Source Toolkit for Building Conversational Recommender Systemcited by 34
38 more
  1. 2021Knowledge-Grounded Dialogue Generation with a Unified Knowledge Representationcited by 32
  2. 2022A Unified Multi-task Learning Framework for Multi-goal Conversational Recommender Systemscited by 32
  3. 2023A Large Language Model Enhanced Conversational Recommender Systemcited by 31
  4. 2022User-Centric Conversational Recommendation with Multi-Aspect User Modelingcited by 29
  5. 2021Improving Conversational Recommendation Systems' Quality with Context-Aware Item Meta Informationcited by 26
  6. 2024How Reliable is Your Simulator? Analysis on the Limitations of Current LLM-based User Simulators for Conversational Recommendationcited by 26
  7. 2022C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender Systemcited by 24
  8. 2021Learning Neural Templates for Recommender Dialogue Systemcited by 22
  9. 2022Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendationcited by 22
  10. 2024A Survey of Conversational Searchcited by 22
  11. 2022BARCOR: Towards A Unified Framework for Conversational Recommendation Systemscited by 21
  12. 2024Bayesian Optimization with LLM-Based Acquisition Functions for Natural Language Preference Elicitationcited by 17
  13. 2023TREA: Tree-Structure Reasoning Schema for Conversational Recommendationcited by 15
  14. 2023Conversational Recommender System and Large Language Model Are Made for Each Other in E-commerce Pre-sales Dialoguecited by 15
  15. 2021KECRS: Towards Knowledge-Enriched Conversational Recommendation Systemcited by 14
  16. 2021RecInDial: A Unified Framework for Conversational Recommendation with Pretrained Language Modelscited by 14
  17. 2023Recent Developments in Recommender Systems: A Surveycited by 14
  18. 2022Comparison-based Conversational Recommender System with Relative Bandit Feedbackcited by 12
  19. 2023U-NEED: A Fine-grained Dataset for User Needs-Centric E-commerce Conversational Recommendationcited by 12
  20. 2024A LLM-based Controllable, Scalable, Human-Involved User Simulator Framework for Conversational Recommender Systemscited by 12
  21. 2023Improving Conversational Recommendation Systems via Bias Analysis and Language-Model-Enhanced Data Augmentationcited by 11
  22. 2024Behavior Alignment: A New Perspective of Evaluating LLM-based Conversational Recommender Systemscited by 11
  23. 2022Bundle MCR: Towards Conversational Bundle Recommendationcited by 10
  24. 2022Hierarchical Conversational Preference Elicitation with Bandit Feedbackcited by 10
  25. 2023Improving Conversational Recommendation Systems via Counterfactual Data Simulationcited by 10
  26. 2024Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendationcited by 10
  27. 2025Graph Retrieval-Augmented LLM for Conversational Recommendation Systemscited by 10
  28. 2022Conversational Recommendation: A Grand AI Challengecited by 9
  29. 2024Parameter-Efficient Conversational Recommender System as a Language Processing Taskcited by 9
  30. 2024Concept -- An Evaluation Protocol on Conversational Recommender Systems with System-centric and User-centric Factorscited by 9
  31. 2024Towards Empathetic Conversational Recommender Systemscited by 9
  32. 2021Recommender systems based on graph embedding techniques: A comprehensive reviewcited by 8
  33. 2022Follow Me: Conversation Planning for Target-driven Recommendation Dialogue Systemscited by 8
  34. 2022Aligning Recommendation and Conversation via Dual Imitationcited by 6
  35. 2023Knowledge Graphs and Pre-trained Language Models enhanced Representation Learning for Conversational Recommender Systemscited by 6
  36. 2021TopicRefine: Joint Topic Prediction and Dialogue Response Generation for Multi-turn End-to-End Dialogue Systemcited by 5
  37. 2023Multi-grained Hypergraph Interest Modeling for Conversational Recommendationcited by 5
  38. 2023Alleviating the Long-Tail Problem in Conversational Recommender Systemscited by 5

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