mlsanityData to 14 Oct 2026

RevCore: Review-augmented Conversational Recommendation

arXiv 2106.00957 ↗First posted 2 Jun 2021cs.CLcited by 47

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Abstract (arXiv)

Existing conversational recommendation (CR) systems usually suffer from insufficient item information when conducted on short dialogue history and unfamiliar items. Incorporating external information (e.g., reviews) is a potential solution to alleviate this problem. Given that reviews often provide a rich and detailed user experience on different interests, they are potential ideal resources for providing high-quality recommendations within an informative conversation. In this paper, we design a novel end-to-end framework, namely, Review-augmented Conversational Recommender (RevCore), where reviews are seamlessly incorporated to enrich item information and assist in generating both coherent and informative responses. In detail, we extract sentiment-consistent reviews, perform review-enriched and entity-based recommendations for item suggestions, as well as use a review-attentive encoder-decoder for response generation. Experimental results demonstrate the superiority of our approach in yielding better performance on both recommendation and conversation responding.

Key facts. Cited by 47 papers in the map (data through 14 Oct 2026). Builds on 30 of its 56 references that are in the map. First posted on arXiv 2 Jun 2021.

Builds on

30 of 56 references.

References · 30

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  10. 2018Towards Deep Conversational Recommendationscited by 176
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18 more
  1. 2020Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusioncited by 122
  2. 2018Conversational Recommender Systemcited by 115
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 2; 2022: 10; 2023: 14; 2024: 10; 2025: 7; 2026: 4.

47 papers.

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  1. 2024A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Modelscited by 452
  2. 2023Large Language Models as Zero-Shot Conversational Recommenderscited by 127
  3. 2022Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learningcited by 86
  4. 2024A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)cited by 58
  5. 2022A Unified Multi-task Learning Framework for Multi-goal Conversational Recommender Systemscited by 32
  6. 2022User-Centric Conversational Recommendation with Multi-Aspect User Modelingcited by 29
  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. 2022BARCOR: Towards A Unified Framework for Conversational Recommendation Systemscited by 21
  10. 2021RoR: Read-over-Read for Long Document Machine Reading Comprehensioncited by 15
  11. 2023TREA: Tree-Structure Reasoning Schema for Conversational Recommendationcited by 15
  12. 2023U-NEED: A Fine-grained Dataset for User Needs-Centric E-commerce Conversational Recommendationcited by 12
35 more
  1. 2023Improving Conversational Recommendation Systems via Counterfactual Data Simulationcited by 10
  2. 2024Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendationcited by 10
  3. 2024Parameter-Efficient Conversational Recommender System as a Language Processing Taskcited by 9
  4. 2024Towards Empathetic Conversational Recommender Systemscited by 9
  5. 2022Aligning Recommendation and Conversation via Dual Imitationcited by 6
  6. 2023Knowledge Graphs and Pre-trained Language Models enhanced Representation Learning for Conversational Recommender Systemscited by 6
  7. 2023Multi-grained Hypergraph Interest Modeling for Conversational Recommendationcited by 5
  8. 2023Alleviating the Long-Tail Problem in Conversational Recommender Systemscited by 5
  9. 2024Knowledge-Enhanced Conversational Recommendation via Transformer-based Sequential Modellingcited by 5
  10. 2025Why Multi-Interest Fairness Matters: Hypergraph Contrastive Multi-Interest Learning for Fair Conversational Recommender Systemcited by 5
  11. 2025Beyond Single Labels: Improving Conversational Recommendation through LLM-Powered Data Augmentationcited by 5
  12. 2022COLA: Improving Conversational Recommender Systems by Collaborative Augmentationcited by 4
  13. 2023Towards Explainable Conversational Recommender Systemscited by 4
  14. 2023Towards a Unified Conversational Recommendation System: Multi-task Learning via Contextualized Knowledge Distillationcited by 4
  15. 2024The Future of Cognitive Strategy-enhanced Persuasive Dialogue Agents: New Perspectives and Trendscited by 4
  16. 2024Enhancing Tourism Recommender Systems for Sustainable City Trips Using Retrieval-Augmented Generationcited by 4
  17. 2024Reasoning over User Preferences: Knowledge Graph-Augmented LLMs for Explainable Conversational Recommendationscited by 4
  18. 2023A Conversation is Worth A Thousand Recommendations: A Survey of Holistic Conversational Recommender Systemscited by 3
  19. 2025LLMs for Supply Chain Managementcited by 3
  20. 2026Retrieval Augmented Conversational Recommendation with Reinforcement Learningcited by 3
  21. 2022EGCR: Explanation Generation for Conversational Recommendationcited by 2
  22. 2022Improving Conversational Recommender System via Contextual and Time-Aware Modeling with Less Domain-Specific Knowledgecited by 2
  23. 2023AUGUST: an Automatic Generation Understudy for Synthesizing Conversational Recommendation Datasetscited by 2
  24. 2023Improving Items and Contexts Understanding with Descriptive Graph for Conversational Recommendationcited by 1
  25. 2023Conversational Recommendation as Retrieval: A Simple, Strong Baselinecited by 1
  26. 2025Multi-Type Context-Aware Conversational Recommender Systems via Mixture-of-Expertscited by 1
  27. 2026HyCoRec: Hypergraph-Enhanced Multi-Preference Learning for Alleviating Matthew Effect in Conversational Recommendationcited by 1
  28. 2022Customized Conversational Recommender Systemscited by 0
  29. 2023Extraction of Atypical Aspects from Customer Reviews: Datasets and Experiments with Language Modelscited by 0
  30. 2024A General and Flexible Multi-concept Parsing Framework for Multilingual Semantic Matchingcited by 0
  31. 2025LumiCRS: Asymmetric Contrastive Prototype Learning for Long-Tail Conversational Recommender Systemscited by 0
  32. 2025STEP: Stepwise Curriculum Learning for Context-Knowledge Fusion in Conversational Recommendationcited by 0
  33. 2025Enhancing Conversational Recommender Systems with Tree-Structured Knowledge and Pretrained Language Modelscited by 0
  34. 2026A Graph-Enhanced Defense Framework for Explainable Fake News Detection with LLMcited by 0
  35. 2026FacetCRS: Multi-Faceted Preference Learning for Pricking Filter Bubbles in Conversational Recommender Systemcited by 0