mlsanityData to 7 Oct 2026

Is MultiWOZ a Solved Task? An Interactive TOD Evaluation Framework with User Simulator

arXiv 2210.14529 ↗First posted 26 Oct 2022cs.CLcited by 15

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Abstract (arXiv)

Task-Oriented Dialogue (TOD) systems are drawing more and more attention in recent studies. Current methods focus on constructing pre-trained models or fine-tuning strategies while the evaluation of TOD is limited by a policy mismatch problem. That is, during evaluation, the user utterances are from the annotated dataset while these utterances should interact with previous responses which can have many alternatives besides annotated texts. Therefore, in this work, we propose an interactive evaluation framework for TOD. We first build a goal-oriented user simulator based on pre-trained models and then use the user simulator to interact with the dialogue system to generate dialogues. Besides, we introduce a sentence-level and a session-level score to measure the sentence fluency and session coherence in the interactive evaluation. Experimental results show that RL-based TOD systems trained by our proposed user simulator can achieve nearly 98% inform and success rates in the interactive evaluation of MultiWOZ dataset and the proposed scores measure the response quality besides the inform and success rates. We are hoping that our work will encourage simulator-based interactive evaluations in the TOD task.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 22 of its 30 references that are in the map. First posted on arXiv 26 Oct 2022.

Builds on

22 of 30 references.

References · 22

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  4. 2020BLEURT: Learning Robust Metrics for Text Generationcited by 1,196
  5. 2018MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modellingcited by 760
  6. 2021BARTScore: Evaluating Generated Text as Text Generationcited by 719
  7. 2019Evaluating the Factual Consistency of Abstractive Text Summarizationcited by 578
  8. 2020Pre-trained Models for Natural Language Processing: A Surveycited by 504
  9. 2020A Simple Language Model for Task-Oriented Dialoguecited by 331
  10. 2016A Network-based End-to-End Trainable Task-oriented Dialogue Systemcited by 252
  11. 2021Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue Systemcited by 139
  12. 2017Key-Value Retrieval Networks for Task-Oriented Dialoguecited by 137
10 more
  1. 2020UBAR: Towards Fully End-to-End Task-Oriented Dialog Systems with GPT-2cited by 111
  2. 2021GALAXY: A Generative Pre-trained Model for Task-Oriented Dialog with Semi-Supervised Learning and Explicit Policy Injectioncited by 102
  3. 2017RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systemscited by 88
  4. 2016A User Simulator for Task-Completion Dialoguescited by 56
  5. 2018Global-Locally Self-Attentive Dialogue State Trackercited by 45
  6. 2019How to Build User Simulators to Train RL-based Dialog Systemscited by 44
  7. 2019Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attentioncited by 43
  8. 2021Transferable Dialogue Systems and User Simulatorscited by 35
  9. 2019ConvLab: Multi-Domain End-to-End Dialog System Platformcited by 29
  10. 2020Multi-Agent Task-Oriented Dialog Policy Learning with Role-Aware Reward Decompositioncited by 23

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Citing papers per year: 2022: 1; 2023: 3; 2024: 2; 2025: 6; 2026: 3.

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