Picture for Nina Lopatina

Nina Lopatina

MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset

Add code
Oct 09, 2020
Figure 1 for MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset
Figure 2 for MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset
Figure 3 for MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset
Figure 4 for MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset
Viaarxiv icon

A general approach to bridge the reality-gap

Add code
Sep 03, 2020
Figure 1 for A general approach to bridge the reality-gap
Figure 2 for A general approach to bridge the reality-gap
Figure 3 for A general approach to bridge the reality-gap
Figure 4 for A general approach to bridge the reality-gap
Viaarxiv icon

Reducing audio membership inference attack accuracy to chance: 4 defenses

Add code
Oct 31, 2019
Figure 1 for Reducing audio membership inference attack accuracy to chance: 4 defenses
Figure 2 for Reducing audio membership inference attack accuracy to chance: 4 defenses
Figure 3 for Reducing audio membership inference attack accuracy to chance: 4 defenses
Figure 4 for Reducing audio membership inference attack accuracy to chance: 4 defenses
Viaarxiv icon

Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks

Add code
Jun 15, 2019
Figure 1 for Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks
Figure 2 for Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks
Figure 3 for Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks
Figure 4 for Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks
Viaarxiv icon