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INSPIRED: Toward Sociable Recommendation Dialog Systems

arXiv 2009.14306 ↗First posted 29 Sep 2020cs.CLcited by 91

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Abstract (arXiv)

In recommendation dialogs, humans commonly disclose their preference and make recommendations in a friendly manner. However, this is a challenge when developing a sociable recommendation dialog system, due to the lack of dialog dataset annotated with such sociable strategies. Therefore, we present INSPIRED, a new dataset of 1,001 human-human dialogs for movie recommendation with measures for successful recommendations. To better understand how humans make recommendations in communication, we design an annotation scheme related to recommendation strategies based on social science theories and annotate these dialogs. Our analysis shows that sociable recommendation strategies, such as sharing personal opinions or communicating with encouragement, more frequently lead to successful recommendations. Based on our dataset, we train end-to-end recommendation dialog systems with and without our strategy labels. In both automatic and human evaluation, our model with strategy incorporation outperforms the baseline model. This work is a first step for building sociable recommendation dialog systems with a basis of social science theories.

Key facts. Cited by 91 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Sep 2020.

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Citing papers per year: 2021: 10; 2022: 13; 2023: 18; 2024: 18; 2025: 19; 2026: 13.

91 papers.

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  1. 2023Large Language Models as Zero-Shot Conversational Recommenderscited by 126
  2. 2021Advances and Challenges in Conversational Recommender Systems: A Surveycited by 118
  3. 2022Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learningcited by 85
  4. 2023Leveraging Large Language Models in Conversational Recommender Systemscited by 63
  5. 2024A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)cited by 58
  6. 2021DuRecDial 2.0: A Bilingual Parallel Corpus for Conversational Recommendationcited by 46
  7. 2021CRSLab: An Open-Source Toolkit for Building Conversational Recommender Systemcited by 34
  8. 2021Knowledge-Grounded Dialogue Generation with a Unified Knowledge Representationcited by 32
  9. 2022A Unified Multi-task Learning Framework for Multi-goal Conversational Recommender Systemscited by 32
  10. 2021Improving Conversational Recommendation Systems' Quality with Context-Aware Item Meta Informationcited by 26
  11. 2021Learning Neural Templates for Recommender Dialogue Systemcited by 22
  12. 2023DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AIcited by 21
38 more
  1. 2024Self-Updatable Large Language Models by Integrating Context into Model Parameterscited by 21
  2. 2023Conversational Recommender System and Large Language Model Are Made for Each Other in E-commerce Pre-sales Dialoguecited by 15
  3. 2024Pearl: A Review-driven Persona-Knowledge Grounded Conversational Recommendation Datasetcited by 15
  4. 2021KECRS: Towards Knowledge-Enriched Conversational Recommendation Systemcited by 14
  5. 2021RecInDial: A Unified Framework for Conversational Recommendation with Pretrained Language Modelscited by 14
  6. 2023U-NEED: A Fine-grained Dataset for User Needs-Centric E-commerce Conversational Recommendationcited by 12
  7. 2022Werewolf Among Us: A Multimodal Dataset for Modeling Persuasion Behaviors in Social Deduction Gamescited by 11
  8. 2024Behavior Alignment: A New Perspective of Evaluating LLM-based Conversational Recommender Systemscited by 11
  9. 2024The Imperative of Conversation Analysis in the Era of LLMs: A Survey of Tasks, Techniques, and Trendscited by 11
  10. 2023Improving Conversational Recommendation Systems via Counterfactual Data Simulationcited by 10
  11. 2024Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendationcited by 10
  12. 2025Wizard of Shopping: Target-Oriented E-commerce Dialogue Generation with Decision Tree Branchingcited by 10
  13. 2025Graph Retrieval-Augmented LLM for Conversational Recommendation Systemscited by 10
  14. 2025Malicious LLM-Based Conversational AI Makes Users Reveal Personal Informationcited by 10
  15. 2026ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenderscited by 10
  16. 2022Conversational Recommendation: A Grand AI Challengecited by 9
  17. 2023Talk the Walk: Synthetic Data Generation for Conversational Music Recommendationcited by 9
  18. 2024Parameter-Efficient Conversational Recommender System as a Language Processing Taskcited by 9
  19. 2024Concept -- An Evaluation Protocol on Conversational Recommender Systems with System-centric and User-centric Factorscited by 9
  20. 2024Injecting Salesperson's Dialogue Strategies in Large Language Models with Chain-of-Thought Reasoningcited by 9
  21. 2025In-context Ranking Preference Optimizationcited by 9
  22. 2022Follow Me: Conversation Planning for Target-driven Recommendation Dialogue Systemscited by 8
  23. 2024Incorporating External Knowledge and Goal Guidance for LLM-based Conversational Recommender Systemscited by 8
  24. 2022Aligning Recommendation and Conversation via Dual Imitationcited by 6
  25. 2023Beyond Single Items: Exploring User Preferences in Item Sets with the Conversational Playlist Curation Datasetcited by 6
  26. 2023Knowledge Graphs and Pre-trained Language Models enhanced Representation Learning for Conversational Recommender Systemscited by 6
  27. 2024Target-constrained Bidirectional Planning for Generation of Target-oriented Proactive Dialoguecited by 6
  28. 2024Simulating Task-Oriented Dialogues with State Transition Graphs and Large Language Modelscited by 6
  29. 2022OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking Experiencecited by 5
  30. 2023Alleviating the Long-Tail Problem in Conversational Recommender Systemscited by 5
  31. 2025Search-Based Interaction For Conversation Recommendation via Generative Reward Model Based Simulated Usercited by 5
  32. 2022INSPIRED2: An Improved Dataset for Sociable Conversational Recommendationcited by 4
  33. 2022COLA: Improving Conversational Recommender Systems by Collaborative Augmentationcited by 4
  34. 2023Towards Explainable Conversational Recommender Systemscited by 4
  35. 2024The Future of Cognitive Strategy-enhanced Persuasive Dialogue Agents: New Perspectives and Trendscited by 4
  36. 2024Reasoning over User Preferences: Knowledge Graph-Augmented LLMs for Explainable Conversational Recommendationscited by 4
  37. 2025LaViC: Adapting Large Vision-Language Models to Visually-Aware Conversational Recommendationcited by 4
  38. 2025Beyond Single Labels: Improving Conversational Recommendation through LLM-Powered Data Augmentationcited by 4

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