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2011.08908
Cited By

SHIELD: Defending Textual Neural Networks against Multiple Black-Box
Adversarial Attacks with Stochastic Multi-Expert Patcher

v1v2 (latest)

SHIELD: Defending Textual Neural Networks against Multiple Black-Box Adversarial Attacks with Stochastic Multi-Expert Patcher

Annual Meeting of the Association for Computational Linguistics (ACL), 2020

17 November 2020

ArXiv (abs)PDF HTML

Papers citing "SHIELD: Defending Textual Neural Networks against Multiple Black-Box Adversarial Attacks with Stochastic Multi-Expert Patcher"

12 / 12 papers shown

Risks, Causes, and Mitigations of Widespread Deployments of Large
Language Models (LLMs): A Survey

Risks, Causes, and Mitigations of Widespread Deployments of Large Language Models (LLMs): A Survey

Md. Nazmus Sakib

Md Athikul Islam

Md Mashrur Arifin

323

13

0

01 Aug 2024

HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack
on Text

HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text

287

24

0

02 Feb 2024

Alert-ME: An Explainability-Driven Defense Against Adversarial Examples in Transformer-Based Text Classification

Alert-ME: An Explainability-Driven Defense Against Adversarial Examples in Transformer-Based Text ClassificationIEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2023

Sharif Abuadbba

Muhammad Ali Babar

526

10

0

03 Jul 2023

Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by
Rewriting Text

Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting TextAnnual Meeting of the Association for Computational Linguistics (ACL), 2023

Alakananda Vempala

250

12

0

25 May 2023

Granular-ball computing: an efficient, robust, and interpretable
adaptive multi-granularity representation and computation method

Granular-ball computing: an efficient, robust, and interpretable adaptive multi-granularity representation and computation method

Xinbo Gao

278

22

0

21 Apr 2023

TextShield: Beyond Successfully Detecting Adversarial Sentences in Text
Classification

TextShield: Beyond Successfully Detecting Adversarial Sentences in Text ClassificationInternational Conference on Learning Representations (ICLR), 2023

Lingfeng Shen

471

10

0

03 Feb 2023

On the Security Vulnerabilities of Text-to-SQL Models

On the Security Vulnerabilities of Text-to-SQL ModelsIEEE International Symposium on Software Reliability Engineering (ISSRE), 2022

390

11

0

28 Nov 2022

Identifying Human Strategies for Generating Word-Level Adversarial
Examples

Identifying Human Strategies for Generating Word-Level Adversarial ExamplesConference on Empirical Methods in Natural Language Processing (EMNLP), 2022

Maximilian Mozes

Bennett Kleinberg

Lewis D. Griffin

366

2

0

20 Oct 2022

ROSE: Robust Selective Fine-tuning for Pre-trained Language Models

ROSE: Robust Selective Fine-tuning for Pre-trained Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP), 2022

Yankai Lin

Peng Li

Jie Zhou

295

9

0

18 Oct 2022

Improving Question Answering Performance Using Knowledge Distillation
and Active Learning

Improving Question Answering Performance Using Knowledge Distillation and Active LearningEngineering applications of artificial intelligence (EAAI), 2021

Yasaman Boreshban

Seyed Morteza Mirbostani

Gholamreza Ghassem-Sani

Seyed Abolghasem Mirroshandel

Shahin Amiriparian

228

18

0

26 Sep 2021

R&R: Metric-guided Adversarial Sentence Generation

R&R: Metric-guided Adversarial Sentence Generation

Alfredo Cuesta-Infante

Laure Berti-Equille

K. Veeramachaneni

253

8

0

17 Apr 2021

Generating Natural Adversarial Examples

Generating Natural Adversarial Examples

844

653

0

31 Oct 2017

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