Papers by Shuaibo Wang

2 papers
Towards Understanding and Improving Knowledge Distillation for Neural Machine Translation (2023.acl-long)

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Challenge: Existing knowledge distillation techniques for neural machine translation lack special treatment on the top-1 information, which is limiting the potential of KD.
Approach: They propose a method to distill knowledge from top-1 predictions of teachers and a technique to infuse more additional knowledge by distilling on the data without ground-truth targets.
Outcome: The proposed method outperforms the vanilla word-level KD and outperfies the existing methods on three different students with different capacity gaps.
Adversarially Improving NMT Robustness to ASR Errors with Confusion Sets (2022.aacl-short)

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Challenge: Existing methods for robustness against homophone errors are limited to homophones . substitution errors are the most common errors in NMT models .
Approach: They propose an adversarial example generation method based on confusion sets that contain words easily confusable with a target word by ASR to conduct adversarially training for NMT models.
Outcome: The proposed method improves on the clean test set and can be used in real-world scenarios.

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