mlsanityData to 7 Oct 2026

Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding

arXiv 1807.01554 ↗First posted 4 Jul 2018cs.CL cs.AIcited by 67

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Abstract (arXiv)

In this paper, we study the problem of data augmentation for language understanding in task-oriented dialogue system. In contrast to previous work which augments an utterance without considering its relation with other utterances, we propose a sequence-to-sequence generation based data augmentation framework that leverages one utterance's same semantic alternatives in the training data. A novel diversity rank is incorporated into the utterance representation to make the model produce diverse utterances and these diversely augmented utterances help to improve the language understanding module. Experimental results on the Airline Travel Information System dataset and a newly created semantic frame annotation on Stanford Multi-turn, Multidomain Dialogue Dataset show that our framework achieves significant improvements of 6.38 and 10.04 F-scores respectively when only a training set of hundreds utterances is represented. Case studies also confirm that our method generates diverse utterances.

Key facts. Cited by 67 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Jul 2018.

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Citing papers per year: 2021: 24; 2022: 14; 2023: 19; 2024: 6; 2025: 2; 2026: 2.

67 papers.

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  1. 2021A Survey of Data Augmentation Approaches for NLPcited by 408
  2. 2021GPT3Mix: Leveraging Large-scale Language Models for Text Augmentationcited by 185
  3. 2023Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventionscited by 121
  4. 2021Data Augmentation Approaches in Natural Language Processing: A Surveycited by 82
  5. 2022PromDA: Prompt-based Data Augmentation for Low-Resource NLU Taskscited by 51
  6. 2021Preview, Attend and Review: Schema-Aware Curriculum Learning for Multi-Domain Dialog State Trackingcited by 35
  7. 2021SGD-X: A Benchmark for Robust Generalization in Schema-Guided Dialogue Systemscited by 34
  8. 2021Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsingcited by 32
  9. 2021FlipDA: Effective and Robust Data Augmentation for Few-Shot Learningcited by 32
  10. 2021Substructure Substitution: Structured Data Augmentation for NLPcited by 25
  11. 2022A Model-Agnostic Data Manipulation Method for Persona-based Dialogue Generationcited by 25
  12. 2021GOLD: Improving Out-of-Scope Detection in Dialogues using Data Augmentationcited by 20
38 more
  1. 2021NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-Based Simulationcited by 16
  2. 2021Data Augmentation for Cross-Domain Named Entity Recognitioncited by 14
  3. 2021Unsupervised Contextual Paraphrase Generation using Lexical Control and Reinforcement Learningcited by 10
  4. 2023GDA: Generative Data Augmentation Techniques for Relation Extraction Taskscited by 10
  5. 2023Improving Conversational Recommendation Systems via Counterfactual Data Simulationcited by 10
  6. 2022PSSAT: A Perturbed Semantic Structure Awareness Transferring Method for Perturbation-Robust Slot Fillingcited by 9
  7. 2022Augmenting Multi-Turn Text-to-SQL Datasets with Self-Playcited by 9
  8. 2023A Multi-Task Semantic Decomposition Framework with Task-specific Pre-training for Few-Shot NERcited by 9
  9. 2022Data Augmentation for Low-Resource Quechua ASR Improvementcited by 8
  10. 2024Improving Black-box Robustness with In-Context Rewritingcited by 8
  11. 2024Rephrasing natural text data with different languages and quality levels for Large Language Model pre-trainingcited by 8
  12. 2021Cross-Modal Generative Augmentation for Visual Question Answeringcited by 7
  13. 2021SpliceOut: A Simple and Efficient Audio Augmentation Methodcited by 7
  14. 2024A Comprehensive Study on NLP Data Augmentation for Hate Speech Detection: Legacy Methods, BERT, and LLMscited by 7
  15. 2021N-Shot Learning for Augmenting Task-Oriented Dialogue State Trackingcited by 6
  16. 2021Learning to Bridge Metric Spaces: Few-shot Joint Learning of Intent Detection and Slot Fillingcited by 6
  17. 2022Text-To-Speech Data Augmentation for Low Resource Speech Recognitioncited by 6
  18. 2022Entity-to-Text based Data Augmentation for various Named Entity Recognition Taskscited by 6
  19. 2022Counterfactual Data Augmentation via Perspective Transition for Open-Domain Dialoguescited by 6
  20. 2024Inductive-Deductive Strategy Reuse for Multi-Turn Instructional Dialoguescited by 6
  21. 2024DiagESC: Dialogue Synthesis for Integrating Depression Diagnosis into Emotional Support Conversationcited by 6
  22. 2021Virtual Data Augmentation: A Robust and General Framework for Fine-tuning Pre-trained Modelscited by 5
  23. 2022Semantic-based Data Augmentation for Math Word Problemscited by 5
  24. 2023Steerable Equivariant Representation Learningcited by 5
  25. 2021SYNERGY: Building Task Bots at Scale Using Symbolic Knowledge and Machine Teachingcited by 3
  26. 2022End-to-End Spoken Language Understanding: Performance analyses of a voice command task in a low resource settingcited by 3
  27. 2022Are Current Task-oriented Dialogue Systems Able to Satisfy Impolite Users?cited by 3
  28. 2022Data Augmentation using Transformers and Similarity Measures for Improving Arabic Text Classificationcited by 3
  29. 2023Learning towards Selective Data Augmentation for Dialogue Generationcited by 3
  30. 2023Boosting Event Extraction with Denoised Structure-to-Text Augmentationcited by 3
  31. 2023From Chatter to Matter: Addressing Critical Steps of Emotion Recognition Learning in Task-oriented Dialoguecited by 3
  32. 2025Frustratingly Easy Data Augmentation for Low-Resource ASRcited by 3
  33. 2021Can vectors read minds better than experts? Comparing data augmentation strategies for the automated scoring of children's mindreading abilitycited by 2
  34. 2021Textual Data Distributions: Kullback Leibler Textual Distributions Contrasts on GPT-2 Generated Texts, with Supervised, Unsupervised Learning on Vaccine & Market Topics & Sentimentcited by 2
  35. 2021Improving the Diversity of Unsupervised Paraphrasing with Embedding Outputscited by 2
  36. 2023Mitigating Data Scarcity for Large Language Modelscited by 2
  37. 2023More Robust Schema-Guided Dialogue State Tracking via Tree-Based Paraphrase Rankingcited by 2
  38. 2023Steering Language Generation: Harnessing Contrastive Expert Guidance and Negative Prompting for Coherent and Diverse Synthetic Data Generationcited by 2

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