1 code implementation • 2 Jun 2023 • Hoang-Quoc Nguyen-Son, Seira Hidano, Kazuhide Fukushima, Shinsaku Kiyomoto, Isao Echizen
Specifically, VoteTRANS detects adversarial text by comparing the hard labels of input text and its transformation.
1 code implementation • 12 Oct 2021 • Hoang-Quoc Nguyen-Son, Seira Hidano, Kazuhide Fukushima, Shinsaku Kiyomoto
In terms of misclassified texts, a classifier handles the texts with both incorrect predictions and adversarial texts, which are generated to fool the classifier, which is called a victim.
1 code implementation • NAACL 2021 • Hoang-Quoc Nguyen-Son, Tran Thao, Seira Hidano, Ishita Gupta, Shinsaku Kiyomoto
However, a round-trip translated text is significantly different from the original text or a translated text using a strange translator.
no code implementations • 19 Dec 2019 • Hoang-Quoc Nguyen-Son, Tran Phuong Thao, Seira Hidano, Shinsaku Kiyomoto
Attackers create adversarial text to deceive both human perception and the current AI systems to perform malicious purposes such as spam product reviews and fake political posts.
no code implementations • WS 2019 • Hoang-Quoc Nguyen-Son, Tran Phuong Thao, Seira Hidano, Shinsaku Kiyomoto
The existing methods detected a machine-translated text only using the text's intrinsic content, but they are unsuitable for classifying the machine-translated and human-written texts with the same meanings.
no code implementations • 24 Apr 2019 • Hoang-Quoc Nguyen-Son, Tran Phuong Thao, Seira Hidano, Shinsaku Kiyomoto
We have developed a method matching similar words throughout the paragraph and estimating the paragraph-level coherence, that can identify machine-translated text.
no code implementations • PACLIC 2018 • Hoang-Quoc Nguyen-Son, Ngoc-Dung T. Tieu, Huy H. Nguyen, Junichi Yamagishi, Isao Echizen
We have developed a method for extracting the coherence features from a paragraph by matching similar words in its sentences.
no code implementations • 12 Apr 2018 • Huy H. Nguyen, Ngoc-Dung T. Tieu, Hoang-Quoc Nguyen-Son, Junichi Yamagishi, Isao Echizen
Making computer-generated (CG) images more difficult to detect is an interesting problem in computer graphics and security.