SEPP: Similarity Estimation of Predicted Probabilities for Defending and Detecting Adversarial Text

Hoang-Quoc Nguyen-Son, Seira Hidano, Kazuhide Fukushima, Shinsaku Kiyomoto


Anthology ID:
2021.paclic-1.2
Volume:
Proceedings of the 35th Pacific Asia Conference on Language, Information and Computation
Month:
11
Year:
2021
Address:
Shanghai, China
Venue:
PACLIC
SIG:
Publisher:
Association for Computational Lingustics
Note:
Pages:
11–20
Language:
URL:
https://aclanthology.org/2021.paclic-1.2
DOI:
Bibkey:
Cite (ACL):
Hoang-Quoc Nguyen-Son, Seira Hidano, Kazuhide Fukushima, and Shinsaku Kiyomoto. 2021. SEPP: Similarity Estimation of Predicted Probabilities for Defending and Detecting Adversarial Text. In Proceedings of the 35th Pacific Asia Conference on Language, Information and Computation, pages 11–20, Shanghai, China. Association for Computational Lingustics.
Cite (Informal):
SEPP: Similarity Estimation of Predicted Probabilities for Defending and Detecting Adversarial Text (Nguyen-Son et al., PACLIC 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2021.paclic-1.2.pdf
Data
WiCWord Sense Disambiguation: a Unified Evaluation Framework and Empirical Comparison