Papers with Counterfactual data augmentation
Enhancing Hate Speech Classifiers through a Gradient-assisted Counterfactual Text Generation Strategy (2025.findings-emnlp)
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| Challenge: | Strong attribute control can distort meaning, while prioritizing semantic preservation may weaken attribute alignment. |
| Approach: | They propose a method that restricts accepted samples to text meeting a minimum BERTScore threshold and applies gradient-assisted proposal generation to improve attribute alignment. |
| Outcome: | a new method for counterfactual text generation improves attribute alignment and semantic preservation . the proposed method achieved the best macro F1-score in two of three test sets . |
CORE: A Retrieve-then-Edit Framework for Counterfactual Data Generation (2022.findings-emnlp)
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| Challenge: | Prior work on counterfactual data augmentation only considered restricted classes of perturbations, limiting their effectiveness. |
| Approach: | They propose a retrieval-augmented framework for creating diverse counterfactual perturbations for CDA. |
| Outcome: | Experiments on natural language inference and sentiment analysis show that the proposed framework can be used to encourage diversity in manually authored perturbations. |