mlsanityData to 7 Oct 2026

Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset

arXiv 1909.05855 ↗First posted 12 Sep 2019cs.CLcited by 426

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Cited by 58 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Virtual assistants such as Google Assistant, Alexa and Siri provide a conversational interface to a large number of services and APIs spanning multiple domains. Such systems need to support an ever-increasing number of services with possibly overlapping functionality. Furthermore, some of these services have little to no training data available. Existing public datasets for task-oriented dialogue do not sufficiently capture these challenges since they cover few domains and assume a single static ontology per domain. In this work, we introduce the the Schema-Guided Dialogue (SGD) dataset, containing over 16k multi-domain conversations spanning 16 domains. Our dataset exceeds the existing task-oriented dialogue corpora in scale, while also highlighting the challenges associated with building large-scale virtual assistants. It provides a challenging testbed for a number of tasks including language understanding, slot filling, dialogue state tracking and response generation. Along the same lines, we present a schema-guided paradigm for task-oriented dialogue, in which predictions are made over a dynamic set of intents and slots, provided as input, using their natural language descriptions. This allows a single dialogue system to easily support a large number of services and facilitates simple integration of new services without requiring additional training data. Building upon the proposed paradigm, we release a model for dialogue state tracking capable of zero-shot generalization to new APIs, while remaining competitive in the regular setting.

Key facts. Cited by 426 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Sep 2019.

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Citing papers per year: 2021: 70; 2022: 90; 2023: 87; 2024: 65; 2025: 54; 2026: 60.

426 papers.

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  1. 2022UL2: Unifying Language Learning Paradigmscited by 292
  2. 2024ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilitiescited by 272
  3. 2021The GEM Benchmark: Natural Language Generation, its Evaluation and Metricscited by 239
  4. 2021SPoT: Better Frozen Model Adaptation through Soft Prompt Transfercited by 235
  5. 2024Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalizationcited by 203
  6. 2022BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagecited by 197
  7. 2024WebLINX: Real-World Website Navigation with Multi-Turn Dialoguecited by 177
  8. 2024A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systemscited by 170
  9. 2021ExT5: Towards Extreme Multi-Task Scaling for Transfer Learningcited by 161
  10. 2021Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue Systemcited by 139
  11. 2023Towards Learning a Generalist Model for Embodied Navigationcited by 135
  12. 2021Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Surveycited by 130
38 more
  1. 2023MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problemscited by 128
  2. 2021KLUE: Korean Language Understanding Evaluationcited by 113
  3. 2021KaggleDBQA: Realistic Evaluation of Text-to-SQL Parserscited by 105
  4. 2021GALAXY: A Generative Pre-trained Model for Task-Oriented Dialog with Semi-Supervised Learning and Explicit Policy Injectioncited by 102
  5. 2021Dialogue State Tracking with a Language Model using Schema-Driven Promptingcited by 94
  6. 2021MultiWOZ 2.4: A Multi-Domain Task-Oriented Dialogue Dataset with Essential Annotation Corrections to Improve State Tracking Evaluationcited by 86
  7. 2021Action-Based Conversations Dataset: A Corpus for Building More In-Depth Task-Oriented Dialogue Systemscited by 73
  8. 2023SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agentscited by 71
  9. 2021Few-Shot Bot: Prompt-Based Learning for Dialogue Systemscited by 64
  10. 2023Leveraging Large Language Models in Conversational Recommender Systemscited by 63
  11. 2024Seal-Tools: Self-Instruct Tool Learning Dataset for Agent Tuning and Detailed Benchmarkcited by 62
  12. 2021Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue State Trackingcited by 61
  13. 2025QuestBench: Can LLMs ask the right question to acquire information in reasoning tasks?cited by 56
  14. 2021BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modelingcited by 55
  15. 2021SIMMC 2.0: A Task-oriented Dialog Dataset for Immersive Multimodal Conversationscited by 54
  16. 2021Zero-Shot Dialogue State Tracking via Cross-Task Transfercited by 52
  17. 2022Rethinking Explainability as a Dialogue: A Practitioner's Perspectivecited by 52
  18. 2023Are LLMs All You Need for Task-Oriented Dialogue?cited by 52
  19. 2022Description-Driven Task-Oriented Dialog Modelingcited by 50
  20. 2023EcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commercecited by 48
  21. 2024Recent Advances of Foundation Language Models-based Continual Learning: A Surveycited by 46
  22. 2022Continual Prompt Tuning for Dialog State Trackingcited by 44
  23. 2025PersonaLens: A Benchmark for Personalization Evaluation in Conversational AI Assistantscited by 44
  24. 2022Controllable Dialogue Simulation with In-Context Learningcited by 42
  25. 2022InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuningcited by 39
  26. 2023SGP-TOD: Building Task Bots Effortlessly via Schema-Guided LLM Promptingcited by 39
  27. 2024API-BLEND: A Comprehensive Corpora for Training and Benchmarking API LLMscited by 39
  28. 2022GEMv2: Multilingual NLG Benchmarking in a Single Line of Codecited by 36
  29. 2021Multilingual and Cross-Lingual Intent Detection from Spoken Datacited by 35
  30. 2021SGD-X: A Benchmark for Robust Generalization in Schema-Guided Dialogue Systemscited by 34
  31. 2021TWEETSUMM -- A Dialog Summarization Dataset for Customer Servicecited by 34
  32. 2022SPACE-3: Unified Dialog Model Pre-training for Task-Oriented Dialog Understanding and Generationcited by 34
  33. 2024Large Language Models as Zero-shot Dialogue State Tracker through Function Callingcited by 34
  34. 2025ToolDial: Multi-turn Dialogue Generation Method for Tool-Augmented Language Modelscited by 34
  35. 2023Unlocking the Potential of User Feedback: Leveraging Large Language Model as User Simulator to Enhance Dialogue Systemcited by 32
  36. 2021AuGPT: Auxiliary Tasks and Data Augmentation for End-To-End Dialogue with Pre-Trained Language Modelscited by 31
  37. 2021Annotation Inconsistency and Entity Bias in MultiWOZcited by 30
  38. 2021CINS: Comprehensive Instruction for Few-shot Learning in Task-oriented Dialog Systemscited by 30

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