mlsanityData to 14 Oct 2026

Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models

arXiv 1507.04808 ↗First posted 17 Jul 2015cs.CL cs.AI cs.LGcited by 207

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Abstract (arXiv)

We investigate the task of building open domain, conversational dialogue systems based on large dialogue corpora using generative models. Generative models produce system responses that are autonomously generated word-by-word, opening up the possibility for realistic, flexible interactions. In support of this goal, we extend the recently proposed hierarchical recurrent encoder-decoder neural network to the dialogue domain, and demonstrate that this model is competitive with state-of-the-art neural language models and back-off n-gram models. We investigate the limitations of this and similar approaches, and show how its performance can be improved by bootstrapping the learning from a larger question-answer pair corpus and from pretrained word embeddings.

Key facts. Cited by 207 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Jul 2015.

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Citing papers per year: 2018: 1; 2019: 2; 2020: 1; 2021: 87; 2022: 56; 2023: 31; 2024: 13; 2025: 14; 2026: 2.

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  1. 2019Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialogcited by 284
  2. 2024A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systemscited by 170
  3. 2021Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Surveycited by 130
  4. 2022Why Exposure Bias Matters: An Imitation Learning Perspective of Error Accumulation in Language Generationcited by 108
  5. 2021Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Groundingcited by 106
  6. 2020Human-centric Dialog Training via Offline Reinforcement Learningcited by 93
  7. 2023On the Possibilities of AI-Generated Text Detectioncited by 88
  8. 2021Anticipating Safety Issues in E2E Conversational AI: Framework and Toolingcited by 78
  9. 2025A Survey of Personalized Large Language Models: Progress and Future Directionscited by 71
  10. 2022Latent Diffusion Energy-Based Model for Interpretable Text Modelingcited by 67
  11. 2022MMDialog: A Large-scale Multi-turn Dialogue Dataset Towards Multi-modal Open-domain Conversationcited by 56
  12. 2023Multi-Party Chat: Conversational Agents in Group Settings with Humans and Modelscited by 54
38 more
  1. 2022Less is More: Learning to Refine Dialogue History for Personalized Dialogue Generationcited by 47
  2. 2021Conversations Are Not Flat: Modeling the Dynamic Information Flow across Dialogue Utterancescited by 40
  3. 2021One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profilescited by 39
  4. 2021MPC-BERT: A Pre-Trained Language Model for Multi-Party Conversation Understandingcited by 36
  5. 2021Transferable Dialogue Systems and User Simulatorscited by 36
  6. 2021CRSLab: An Open-Source Toolkit for Building Conversational Recommender Systemcited by 34
  7. 2021TWEETSUMM -- A Dialog Summarization Dataset for Customer Servicecited by 34
  8. 2024SALMONN-omni: A Codec-free LLM for Full-duplex Speech Understanding and Generationcited by 33
  9. 2021Multimodal Dialogue Response Generationcited by 32
  10. 2021Conversational Question Answering: A Surveycited by 31
  11. 2021Semi-Supervised Variational Reasoning for Medical Dialogue Generationcited by 30
  12. 2021Commonsense-Focused Dialogues for Response Generation: An Empirical Studycited by 30
  13. 2025SALMONN-omni: A Standalone Speech LLM without Codec Injection for Full-duplex Conversationcited by 27
  14. 2023RECAP: Retrieval-Enhanced Context-Aware Prefix Encoder for Personalized Dialogue Response Generationcited by 25
  15. 2021Conversational Question Answering over Knowledge Graphs with Transformer and Graph Attention Networkscited by 24
  16. 2022C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender Systemcited by 24
  17. 2021Learning Neural Templates for Recommender Dialogue Systemcited by 22
  18. 2018Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learningcited by 21
  19. 2021Emotion-aware Chat Machine: Automatic Emotional Response Generation for Human-like Emotional Interactioncited by 21
  20. 2021End-to-End Learning of Flowchart Grounded Task-Oriented Dialogscited by 20
  21. 2021Maria: A Visual Experience Powered Conversational Agentcited by 19
  22. 2021Investigating Robustness of Dialog Models to Popular Figurative Language Constructscited by 19
  23. 2022A Personalized Dialogue Generator with Implicit User Persona Detectioncited by 19
  24. 2022Why is constrained neural language generation particularly challenging?cited by 19
  25. 2021Generating Relevant and Coherent Dialogue Responses using Self-separated Conditional Variational AutoEncoderscited by 18
  26. 2022FADO: Feedback-Aware Double COntrolling Network for Emotional Support Conversationcited by 18
  27. 2021Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systemscited by 17
  28. 2021Thinking Clearly, Talking Fast: Concept-Guided Non-Autoregressive Generation for Open-Domain Dialogue Systemscited by 17
  29. 2021GTM: A Generative Triple-Wise Model for Conversational Question Generationcited by 16
  30. 2021Synthesizing Adversarial Negative Responses for Robust Response Ranking and Evaluationcited by 16
  31. 2022HeterMPC: A Heterogeneous Graph Neural Network for Response Generation in Multi-Party Conversationscited by 16
  32. 2022Multimodal Conversational AI: A Survey of Datasets and Approachescited by 16
  33. 2022A Mixture-of-Expert Approach to RL-based Dialogue Managementcited by 16
  34. 2022Measuring and Improving Semantic Diversity of Dialogue Generationcited by 16
  35. 2021TextBox: A Unified, Modularized, and Extensible Framework for Text Generationcited by 15
  36. 2021Partner Matters! An Empirical Study on Fusing Personas for Personalized Response Selection in Retrieval-Based Chatbotscited by 15
  37. 2021Automatically Select Emotion for Response via Personality-affected Emotion Transitioncited by 15
  38. 2021Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classificationcited by 15

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