mlsanityData to 14 Oct 2026

KETOD: Knowledge-Enriched Task-Oriented Dialogue

arXiv 2205.05589 ↗First posted 11 May 2022cs.CLcited by 12

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Abstract (arXiv)

Existing studies in dialogue system research mostly treat task-oriented dialogue and chit-chat as separate domains. Towards building a human-like assistant that can converse naturally and seamlessly with users, it is important to build a dialogue system that conducts both types of conversations effectively. In this work, we investigate how task-oriented dialogue and knowledge-grounded chit-chat can be effectively integrated into a single model. To this end, we create a new dataset, KETOD (Knowledge-Enriched Task-Oriented Dialogue), where we naturally enrich task-oriented dialogues with chit-chat based on relevant entity knowledge. We also propose two new models, SimpleToDPlus and Combiner, for the proposed task. Experimental results on both automatic and human evaluations show that the proposed methods can significantly improve the performance in knowledge-enriched response generation while maintaining a competitive task-oriented dialog performance. We believe our new dataset will be a valuable resource for future studies. Our dataset and code are publicly available at urlhttps://github.com/facebookresearch/ketod.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 31 of its 46 references that are in the map. First posted on arXiv 11 May 2022.

Builds on

31 of 46 references.

References · 31

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19 more
  1. 2016Neural Belief Tracker: Data-Driven Dialogue State Trackingcited by 143
  2. 2021Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue Systemcited by 139
  3. 2017A Knowledge-Grounded Neural Conversation Modelcited by 136
  4. 2015Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systemscited by 134
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  9. 2020Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Accesscited by 58
  10. 2018Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systemscited by 53
  11. 2020Adding Chit-Chat to Enhance Task-Oriented Dialoguescited by 48
  12. 2018Global-Locally Self-Attentive Dialogue State Trackercited by 45
  13. 2017Composite Task-Completion Dialogue Policy Learning via Hierarchical Deep Reinforcement Learningcited by 44
  14. 2019DyKgChat: Benchmarking Dialogue Generation Grounding on Dynamic Knowledge Graphscited by 33
  15. 2021"How Robust r u?": Evaluating Task-Oriented Dialogue Systems on Spoken Conversationscited by 30
  16. 2021Fusing task-oriented and open-domain dialogues in conversational agentscited by 28
  17. 2017End-to-End Optimization of Task-Oriented Dialogue Model with Deep Reinforcement Learningcited by 19
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 4; 2023: 5; 2024: 2; 2025: 0; 2026: 1.

12 papers.

  1. 2023A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospectscited by 66
  2. 2024Towards Human-centered Proactive Conversational Agentscited by 49
  3. 2023DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AIcited by 22
  4. 2023"What do others think?": Task-Oriented Conversational Modeling with Subjective Knowledgecited by 6
  5. 2022OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking Experiencecited by 5
  6. 2022Knowledge-grounded Dialog State Trackingcited by 5
  7. 2022Enhancing Task Bot Engagement with Synthesized Open-Domain Dialogcited by 5
  8. 2023UniPCM: Universal Pre-trained Conversation Model with Task-aware Automatic Promptcited by 3
  9. 2024A Unified Approach to Emotion Detection and Task-Oriented Dialogue Modelingcited by 2
  10. 2023Enhancing Task-Oriented Dialogues with Chitchat: a Comparative Study Based on Lexical Diversity and Divergencecited by 1
  11. 2022From Knowledge Augmentation to Multi-tasking: Towards Human-like Dialogue Systemscited by 0
  12. 2026CUEing User Simulators: Calibrated User Embeddings for Multi-Turn Benchmarkingcited by 0