Papers by Puneeth Saladi
Revisiting Robust Neural Machine Translation: A Transformer Case Study (2021.findings-emnlp)
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| Challenge: | Recent advances in NMT have shown promising results but are vulnerable to noise. |
| Approach: | They propose a data-driven technique called Target Augmented Fine-tuning to incorporate noise during training. |
| Outcome: | The proposed techniques perform with no degradation where up to 10% of entire test words are infected by noise. |