mlsanityData to 7 Oct 2026

AllWOZ: Towards Multilingual Task-Oriented Dialog Systems for All

arXiv 2112.08333 ↗First posted 15 Dec 2021cs.CLcited by 9

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Abstract (arXiv)

A commonly observed problem of the state-of-the-art natural language technologies, such as Amazon Alexa and Apple Siri, is that their services do not extend to most developing countries' citizens due to language barriers. Such populations suffer due to the lack of available resources in their languages to build NLP products. This paper presents AllWOZ, a multilingual multi-domain task-oriented customer service dialog dataset covering eight languages: English, Mandarin, Korean, Vietnamese, Hindi, French, Portuguese, and Thai. Furthermore, we create a benchmark for our multilingual dataset by applying mT5 with meta-learning.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 21 of its 31 references that are in the map. First posted on arXiv 15 Dec 2021.

Builds on

21 of 31 references.

References · 21

  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. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,861
  4. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  5. 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,813
  6. 2019Cross-lingual Language Model Pretrainingcited by 1,088
  7. 2020Multilingual Denoising Pre-training for Neural Machine Translationcited by 1,028
  8. 2018MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modellingcited by 760
  9. 2019MASS: Masked Sequence to Sequence Pre-training for Language Generationcited by 345
  10. 2019Massively Multilingual Neural Machine Translation in the Wild: Findings and Challengescited by 253
  11. 2019Massively Multilingual Neural Machine Translationcited by 246
  12. 2020MultiWOZ 2.2 : A Dialogue Dataset with Additional Annotation Corrections and State Tracking Baselinescited by 201
9 more
  1. 2017A Survey Of Cross-lingual Word Embedding Modelscited by 142
  2. 2018Cross-Lingual Transfer Learning for Multilingual Task Oriented Dialogcited by 124
  3. 2021MultiWOZ 2.4: A Multi-Domain Task-Oriented Dialogue Dataset with Essential Annotation Corrections to Improve State Tracking Evaluationcited by 86
  4. 2020Pre-training Multilingual Neural Machine Translation by Leveraging Alignment Informationcited by 64
  5. 2020MultiWOZ 2.3: A multi-domain task-oriented dialogue dataset enhanced with annotation corrections and co-reference annotationcited by 51
  6. 2019Domain Adaptive Dialog Generation via Meta Learningcited by 41
  7. 2021Annotation Inconsistency and Entity Bias in MultiWOZcited by 30
  8. 2019Zero-shot Cross-lingual Dialogue Systems with Transferable Latent Variablescited by 21
  9. 2017Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraintscited by 20

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Citing papers per year: 2022: 5; 2023: 3; 2024: 1.

9 papers.