mlsanityData to 7 Oct 2026

DoCoGen: Domain Counterfactual Generation for Low Resource Domain Adaptation

arXiv 2202.12350 ↗First posted 24 Feb 2022cs.CL cs.AIcited by 36

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Abstract (arXiv)

Natural language processing (NLP) algorithms have become very successful, but they still struggle when applied to out-of-distribution examples. In this paper we propose a controllable generation approach in order to deal with this domain adaptation (DA) challenge. Given an input text example, our DoCoGen algorithm generates a domain-counterfactual textual example (D-con) - that is similar to the original in all aspects, including the task label, but its domain is changed to a desired one. Importantly, DoCoGen is trained using only unlabeled examples from multiple domains - no NLP task labels or parallel pairs of textual examples and their domain-counterfactuals are required. We show that DoCoGen can generate coherent counterfactuals consisting of multiple sentences. We use the D-cons generated by DoCoGen to augment a sentiment classifier and a multi-label intent classifier in 20 and 78 DA setups, respectively, where source-domain labeled data is scarce. Our model outperforms strong baselines and improves the accuracy of a state-of-the-art unsupervised DA algorithm.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). Builds on 40 of its 66 references that are in the map. First posted on arXiv 24 Feb 2022.

Builds on

40 of 66 references.

References · 40

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28 more
  1. 2021A Survey of Data Augmentation Approaches for NLPcited by 408
  2. 2016A Persona-Based Neural Conversation Modelcited by 221
  3. 2021Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Modelscited by 219
  4. 2018Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relationscited by 201
  5. 2021Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyondcited by 177
  6. 2020CausaLM: Causal Model Explanation Through Counterfactual Language Modelscited by 117
  7. 2020If beam search is the answer, what was the question?cited by 114
  8. 2021An Empirical Survey of Data Augmentation for Limited Data Learning in NLPcited by 101
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  10. 2021Competency Problems: On Finding and Removing Artifacts in Language Datacited by 91
  11. 2021Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Testscited by 77
  12. 2021Towards Zero-Label Language Learningcited by 76
  13. 2020Explaining The Efficacy of Counterfactually Augmented Datacited by 64
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  15. 2020Exploring Controllable Text Generation Techniquescited by 55
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Citing papers per year: 2022: 5; 2023: 13; 2024: 10; 2025: 7; 2026: 1.

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  1. 2022Towards Faithful Model Explanation in NLP: A Surveycited by 129
  2. 2022CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behaviorcited by 54
  3. 2023Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactualscited by 44
  4. 2023COCO-Counterfactuals: Automatically Constructed Counterfactual Examples for Image-Text Pairscited by 39
  5. 2023Towards Trustworthy and Aligned Machine Learning: A Data-centric Survey with Causality Perspectivescited by 30
  6. 2024On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMscited by 24
  7. 2024A Survey on Natural Language Counterfactual Generationcited by 21
  8. 2022Example-based Hypernetworks for Out-of-Distribution Generalizationcited by 16
  9. 2023A Systematic Study of Knowledge Distillation for Natural Language Generation with Pseudo-Target Trainingcited by 16
  10. 2023Self-supervised Meta-Prompt Learning with Meta-Gradient Regularization for Few-shot Generalizationcited by 15
  11. 2024CEval: A Benchmark for Evaluating Counterfactual Text Generationcited by 15
  12. 2025AdaptiVocab: Enhancing LLM Efficiency in Focused Domains through Lightweight Vocabulary Adaptationcited by 15
24 more
  1. 2023Data Augmentations for Improved (Large) Language Model Generalizationcited by 14
  2. 2024Counterfactual Generation with Identifiability Guaranteescited by 13
  3. 2023Measuring the Robustness of NLP Models to Domain Shiftscited by 11
  4. 2023An Invariant Learning Characterization of Controlled Text Generationcited by 9
  5. 2023Human Choice Prediction in Language-based Persuasion Games: Simulation-based Off-Policy Evaluationcited by 8
  6. 2023Counterfactuals of Counterfactuals: a back-translation-inspired approach to analyse counterfactual editorscited by 6
  7. 2023VQA-GEN: A Visual Question Answering Benchmark for Domain Generalizationcited by 5
  8. 2024The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoningcited by 5
  9. 2025Zero-Shot and Efficient Clarification Need Prediction in Conversational Searchcited by 4
  10. 2024Explaining Text Classifiers with Counterfactual Representationscited by 3
  11. 2024Domain Generalization via Causal Adjustment for Cross-Domain Sentiment Analysiscited by 3
  12. 2024CAUSE: Counterfactual Assessment of User Satisfaction Estimation in Task-Oriented Dialogue Systemscited by 3
  13. 2024Automated Adversarial Discovery for Safety Classifierscited by 3
  14. 2025Guiding LLMs to Generate High-Fidelity and High-Quality Counterfactual Explanations for Text Classificationcited by 3
  15. 2022Generalizing through Forgetting -- Domain Generalization for Symptom Event Extraction in Clinical Notescited by 2
  16. 2023Robust Stance Detection: Understanding Public Perceptions in Social Mediacited by 2
  17. 2025Multi-Domain Explainability of Preferencescited by 2
  18. 2024Seeing Through VisualBERT: A Causal Adventure on Memetic Landscapescited by 1
  19. 2022Domain Adaptation from Scratchcited by 0
  20. 2023ReMask: A Robust Information-Masking Approach for Domain Counterfactual Generationcited by 0
  21. 2025Admitting Ignorance Helps the Video Question Answering Models to Answercited by 0
  22. 2025Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATEcited by 0
  23. 2025CAuSE: Decoding Multimodal Classifiers using Faithful Natural Language Explanationcited by 0
  24. 2026Gumbel Machine: Counterfactual Student Writing Generation via Gumbel Noise Steeringcited by 0