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CheckHARD: Checking Hard Labels for Adversarial Text Detection, Prediction Correction, and Perturbed Word Suggestion.

, , , , and . EMNLP (Findings), page 2903-2913. Association for Computational Linguistics, (2022)

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An Evaluation Framework for Fastest Oblivious RAM., , and . IoTBDS, page 114-122. SciTePress, (2018)Generating Adversarial Examples for Hardware-Trojan Detection at Gate-Level Netlists., , , , , and . J. Inf. Process., (2021)R-HTDetector: Robust Hardware-Trojan Detection Based on Adversarial Training., , , , and . IEEE Trans. Computers, 72 (2): 333-345 (February 2023)Detecting Machine-Translated Paragraphs by Matching Similar Words., , , and . CICLing (1), volume 13451 of Lecture Notes in Computer Science, page 521-532. Springer, (2019)Text Revealer: Private Text Reconstruction via Model Inversion Attacks against Transformers., , and . CoRR, (2022)Toward Learning Robust Detectors from Imbalanced Datasets Leveraging Weighted Adversarial Training., , , and . CANS, volume 13099 of Lecture Notes in Computer Science, page 392-411. Springer, (2021)Feature-level Approach for the Evaluation of Text Classification Models., , , and . VISIGRAPP (3: IVAPP), page 164-170. SCITEPRESS, (2022)SEPP: Similarity Estimation of Predicted Probabilities for Defending and Detecting Adversarial Text., , , and . PACLIC, page 11-20. Association for Computational Lingustics, (2021)CheckHARD: Checking Hard Labels for Adversarial Text Detection, Prediction Correction, and Perturbed Word Suggestion., , , , and . EMNLP (Findings), page 2903-2913. Association for Computational Linguistics, (2022)Model Inversion Attacks for Prediction Systems: Without Knowledge of Non-Sensitive Attributes., , , , and . PST, page 115-126. IEEE Computer Society, (2017)