mlsanityData to 7 Oct 2026

Training Millions of Personalized Dialogue Agents

arXiv 1809.01984 ↗First posted 6 Sep 2018cs.CLcited by 126

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Abstract (arXiv)

Current dialogue systems are not very engaging for users, especially when trained end-to-end without relying on proactive reengaging scripted strategies. Zhang et al. (2018) showed that the engagement level of end-to-end dialogue models increases when conditioning them on text personas providing some personalized back-story to the model. However, the dataset used in Zhang et al. (2018) is synthetic and of limited size as it contains around 1k different personas. In this paper we introduce a new dataset providing 5 million personas and 700 million persona-based dialogues. Our experiments show that, at this scale, training using personas still improves the performance of end-to-end systems. In addition, we show that other tasks benefit from the wide coverage of our dataset by fine-tuning our model on the data from Zhang et al. (2018) and achieving state-of-the-art results.

Key facts. Cited by 126 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Sep 2018.

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Citing papers per year: 2021: 25; 2022: 27; 2023: 32; 2024: 18; 2025: 13; 2026: 11.

126 papers.

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  1. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  2. 2023LaMP: When Large Language Models Meet Personalizationcited by 425
  3. 2023Tool Learning with Foundation Modelscited by 302
  4. 2023Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Mergingcited by 271
  5. 2021Beyond Goldfish Memory: Long-Term Open-Domain Conversationcited by 266
  6. 2024InfiniGen: Efficient Generative Inference of Large Language Models with Dynamic KV Cache Managementcited by 242
  7. 2021Hash Layers For Large Sparse Modelscited by 236
  8. 2022BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagecited by 197
  9. 2021RedCaps: web-curated image-text data created by the people, for the peoplecited by 175
  10. 2025Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMscited by 142
  11. 2022A Survey of Controllable Text Generation using Transformer-based Pre-trained Language Modelscited by 128
  12. 2022Long Time No See! Open-Domain Conversation with Long-Term Persona Memorycited by 107
38 more
  1. 2022Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completioncited by 102
  2. 2024Optimization Methods for Personalizing Large Language Models through Retrieval Augmentationcited by 98
  3. 2023Pearl: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrieverscited by 91
  4. 2024LongLaMP: A Benchmark for Personalized Long-form Text Generationcited by 91
  5. 2024From Matching to Generation: A Survey on Generative Information Retrievalcited by 89
  6. 2023Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedbackcited by 86
  7. 2021BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Datacited by 75
  8. 2024Large Language Models Empowered Personalized Web Agentscited by 64
  9. 2023Leveraging Large Language Models in Conversational Recommender Systemscited by 63
  10. 2023Recursively Summarizing Enables Long-Term Dialogue Memory in Large Language Modelscited by 62
  11. 2024PersonalLLM: Tailoring LLMs to Individual Preferencescited by 56
  12. 2023Teach LLMs to Personalize -- An Approach inspired by Writing Educationcited by 48
  13. 2023Faithful Persona-based Conversational Dataset Generation with Large Language Modelscited by 45
  14. 2023Learning to Rewrite Prompts for Personalized Text Generationcited by 40
  15. 2023Are Personalized Stochastic Parrots More Dangerous? Evaluating Persona Biases in Dialogue Systemscited by 37
  16. 2022Prompt Injection: Parameterization of Fixed Inputscited by 35
  17. 2023Opportunities and Challenges in Neural Dialog Tutoringcited by 33
  18. 2021Extreme Multi-label Learning for Semantic Matching in Product Searchcited by 28
  19. 2021UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysiscited by 28
  20. 2023LiveChat: A Large-Scale Personalized Dialogue Dataset Automatically Constructed from Live Streamingcited by 27
  21. 2023RECAP: Retrieval-Enhanced Context-Aware Prefix Encoder for Personalized Dialogue Response Generationcited by 25
  22. 2023MPCHAT: Towards Multimodal Persona-Grounded Conversationcited by 24
  23. 2024Modeling Human Subjectivity in LLMs Using Explicit and Implicit Human Factors in Personascited by 23
  24. 2021Am I Me or You? State-of-the-Art Dialogue Models Cannot Maintain an Identitycited by 22
  25. 2022COSPLAY: Concept Set Guided Personalized Dialogue Generation Across Both Party Personascited by 20
  26. 2022Empathic Conversations: A Multi-level Dataset of Contextualized Conversationscited by 20
  27. 2024Personalized Text Generation with Fine-Grained Linguistic Controlcited by 20
  28. 2023PeaCoK: Persona Commonsense Knowledge for Consistent and Engaging Narrativescited by 19
  29. 2024CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language Modelscited by 19
  30. 2024Recent Trends in Personalized Dialogue Generation: A Review of Datasets, Methodologies, and Evaluationscited by 19
  31. 2022TVShowGuess: Character Comprehension in Stories as Speaker Guessingcited by 17
  32. 2022Improving Personality Consistency in Conversation by Persona Extendingcited by 17
  33. 2022Multimodal Conversational AI: A Survey of Datasets and Approachescited by 16
  34. 2023PRODIGy: a PROfile-based DIalogue Generation datasetcited by 16
  35. 2021Partner Matters! An Empirical Study on Fusing Personas for Personalized Response Selection in Retrieval-Based Chatbotscited by 15
  36. 2023Zero-shot Clarifying Question Generation for Conversational Searchcited by 14
  37. 2023TempEL: Linking Dynamically Evolving and Newly Emerging Entitiescited by 14
  38. 2021Telling Stories through Multi-User Dialogue by Modeling Character Relationscited by 13

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