Papers by Liping Yuan
On the Transferability of Adversarial Attacks against Neural Text Classifier (2021.emnlp-main)
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| Challenge: | Existing studies show that deep neural networks are vulnerable to adversarial examples . a small perturbation to an input alters the model prediction . |
| Approach: | They propose a genetic algorithm to find models that can induce adversarial examples to fool models . they propose word replacement rules that can be used for model diagnostics from these examples . |
| Outcome: | The proposed model can fool almost all existing models, while ignoring the data bias in the training set. |
Unsupervised Grammatical Error Correction Rivaling Supervised Methods (2023.emnlp-main)
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| Challenge: | Current state-of-the-art grammatical error correction systems rely on labeled data . current systems require manual correction and require a large quantity of labeles . |
| Approach: | They propose an unsupervised method to build a grammatical error correction system using a fixer and a critic. |
| Outcome: | The proposed system outperforms previous unsupervised systems on English and Chinese GEC. |