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ETHNOS_APP

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Wangli Yang

Dados Biográficos

ID6536664
NOMEWangli Yang
PRENOMESWangli
SOBRENOMEYang
ASSINATURAYANG W
AFILIAÇÕESSchool of Computing and Information Technology, University of Wollongong. [email protected]
VERIFICADONão
TOTAL DE OBRAS1
TOTAL DE CITAÇÕES0
OBRAS COMO AUTOR1
OBRAS COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2025
ANO MAIS RECENTE DE PUBLICAÇÃO2025
ÍNDICE H0
  • Defensive Dual Masking for Robust Adversarial Defense

    Open Access•Wangli Yang, Jie Yang et al.•ARTICLE•Computational Linguistics•2025

    Adversarial defenses for textual data have gained considerable attention in recent years due to the increasing vulnerability of Natural Language Processing (NLP) models to adversarial attacks. These attacks exploit subtle perturbations in input text to deceive models, posing significant challenges to model robustness and reliability. This article introduces Defensive Dual Masking (DDM), a simple yet effective algorithm that uses two unique maskin…

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  • Defensive Dual Masking for Robust Adversarial Defense

    Open Access•Wangli Yang, Jie Yang et al.•ARTICLE•Computational Linguistics•2025

    Adversarial defenses for textual data have gained considerable attention in recent years due to the increasing vulnerability of Natural Language Processing (NLP) models to adversarial attacks. These attacks exploit subtle perturbations in input text to deceive models, posing significant challenges to model robustness and reliability. This article introduces Defensive Dual Masking (DDM), a simple yet effective algorithm that uses two unique maskin…

Adversarial Robustness in Machine Learning (1 obra) · Adversarial system (1 obra) · Exploit (1 obra) · Inference (1 obra) · Masking (illustration (1 obra) · Physical Unclonable Functions (PUFs) and Hardware Security (1 obra) · Robustness (evolution (1 obra) · Scalability (1 obra) · Subspace topology (1 obra)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae