Papers by Doan Vu
Granularity is crucial when applying differential privacy to text: An investigation for neural machine translation (2024.findings-emnlp)
Copied to clipboard
| Challenge: | Differential privacy (DP) is a method that is increasingly popular in NLP but the choice of granularity at which it is applied is often neglected. |
| Approach: | They propose to apply differential privacy (DP) to a neural machine translation dataset to protect individual data points. |
| Outcome: | The proposed method is more resistant to membership inference attacks than the document-level NMT system. |