Towards Evaluating the Robustness of Neural Networks

Carlini, Nicholas, Wagner, David·2017·2017 IEEE Symposium on Security and Privacy (SP)

Cited by (1,019)

Items 901–1,000 of 1,019

  1. Characterizing and Evaluating Adversarial Examples for Offline Handwritten Signature Verification
    Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira · 2019 · IEEE Transactions on Information Forensics and Security
  2. Adversarial Black-Box Attacks on Automatic Speech Recognition Systems Using Multi-Objective Evolutionary Optimization
    Shreya Khare, Rahul Aralikatte, Senthil Mani · 2019 · Interspeech (USB)
  3. VLA
    Meng Shen, Zichen Liao, Liehuang Zhu, Ke Xu, Xiaojiang Du · 2019 · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
  4. Real-Time and Embedded Deep Learning on FPGA for RF Signal Classification
    Sohraab Soltani, Yalin E. Sagduyu, Raqibul Hasan, Kemal Davaslıoğlu, Hongmei Deng, Tugba Erpek · 2019 · IEEE Military Communications Conference (MILCOM)
  5. advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns
    Zhibo Wang, Siyan Zheng, Mengkai Song, Qian Wang, Alireza Rahimpour, Hairong Qi · 2019 · IEEE/CVF International Conference on Computer Vision (ICCV)
  6. Image Transformation based Defense Against Adversarial Perturbation on Deep Learning Models
    Akshay Agarwal, Richa Singh, Mayank Vatsa A, Nalini Ratha · 2020 · IEEE Transactions on Dependable and Secure Computing
  7. GangSweep
    Liuwan Zhu, Rui Ning, Cong Wang, Chunsheng Xin, Hongyi Wu · 2020 · ACM International Conference on Multimedia (ACM MM)
  8. Fairness Through Robustness
    Vedant Nanda, Samuel W. Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson · 2021 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
  9. Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference
    Ting-Kuei Hu, Tianlong Chen, Haotao Wang, Zhangyang Wang · 2020 · arXiv (Cornell University)
  10. Query-efficient Meta Attack to Deep Neural Networks
    Jiawei Du, Hu Zhang, Joey Tianyi Zhou, Yi Yang, Jiashi Feng · 2019 · arXiv (Cornell University)
  11. Towards a Robust Deep Neural Network in Texts: A Survey
    Wenqi Wang, Wang, Run, Wang, Lina, Zhibo Wang, Aoshuang Ye · 2019 · arXiv (Cornell University)
  12. Machine learning in NextG networks via generative adversarial networks
    Ayanoglu, Ender, Davaslioglu, Kemal, Sagduyu, Yalin E. · 2022 · IEEE Transactions on Cognitive Communications and Networking
  13. Tiny noise, big mistakes : adversarial perturbations induce errors in brain-computer interface spellers
    Xiao Li Zhang, Dongrui Wu, Lieyun Ding, Hanbin Luo, Lin, Chin-Teng, Tzyy‐Ping Jung, Ricardo Chavarriaga · 2020 · Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)
  14. Camdar‐adv: Generating adversarial patches on 3D object
    Chang Chen, Teng Huang · 2020 · International Journal of Intelligent Systems
  15. Efficient and Effective Feature Space Exploration for Testing Deep Learning Systems
    Tahereh Zohdinasab, Vincenzo Riccio, Alessio Gambi, Paolo Tonella · 2022 · ACM Transactions on Software Engineering and Methodology
  16. Better Trigger Inversion Optimization in Backdoor Scanning
    Guanhong Tao, Guangyu Shen, Yingqi Liu, Shengwei An, Qiuling Xu, Shiqing Ma, Pan Li, Xiangyu Zhang · 2022 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  17. Adversarial Attack and Defense on Deep Learning for Air Transportation Communication Jamming
    Mingqian Liu, Zhenju Zhang, Yunfei Chen, Jianhua Ge, Nan Zhao · 2023 · IEEE Transactions on Intelligent Transportation Systems
  18. Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation
    Bo Huang, Mingyang Chen, Yi Wang, Junda Lu, Minhao Cheng, Wei Wang · 2023 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  19. A Comprehensive Review and Analysis of Deep Learning-Based Medical Image Adversarial Attack and Defense
    Gladys Wavinya Muoka, Yi Ding, Chiagoziem C. Ukwuoma, Albert Mutale, Chukwuebuka Joseph Ejiyi, Asha Khamis Mzee, Emmanuel S. A. Gyarteng, Ali Alqahtani, Mugahed A. Al–antari · 2023 · Mathematics
  20. Scaleable input gradient regularization for adversarial robustness
    Chris Finlay, Adam M. Oberman · 2020 · Machine Learning with Applications
  21. HeNet: A Deep Learning Approach on Intel® Processor Trace for Effective Exploit Detection
    Li Chen, Salmin Sultana, Ravi Sahita · 2018 · IEEE Security and Privacy Workshops (SPW)
  22. Dissector
    Huiyan Wang, Jingwei Xu, Chang Xu, Xiaoxing Ma, Jian Jiang Lu · 2020 · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
  23. Defending Your Voice: Adversarial Attack on Voice Conversion
    Chien‐Yu Huang, Yist Y. Lin, Hung-yi Lee, Lin-shan Lee · 2021 · IEEE Spoken Language Technology Workshop (SLT)
  24. Training individually fair ML models with Sensitive Subspace Robustness
    Mikhail Yurochkin, Amanda Bower, Yuekai Sun · 2019 · arXiv (Cornell University)
  25. The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples
    Timo Freiesleben · 2021 · Minds and Machines
  26. Generative Adversarial Attacks Against Deep- Learning-Based Camera Model Identification
    Chen Chen, Xinwei Zhao, Matthew Christopher Stamm · 2019 · IEEE Transactions on Information Forensics and Security
  27. Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing
    Xunguang Wang, Zheng Zhang, Baoyuan Wu, Fumin Shen, Guangming Lu · 2021 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  28. Countering Adversarial Attacks on Autonomous Vehicles Using Denoising Techniques: A Review
    Andreas Kloukiniotis, A. Papandreou, Aris S. Lalos, Petros Kapsalas, Duong-Van Nguyen, K. Moustakas · 2022 · IEEE Open Journal of Intelligent Transportation Systems
  29. Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving Scenarios
    Jung Im Choi, Qing Tian · 2022 · IEEE Intelligent Vehicles Symposium
  30. PatchZero: Defending against Adversarial Patch Attacks by Detecting and Zeroing the Patch
    Ke Xu, Yao Xiao, Zhaoheng Zheng, Kaijie Cai, Ram Nevatia · 2023 · IEEE Winter Conference on Applications of Computer Vision
  31. Average Gradient-Based Adversarial Attack
    Chen Wan, Fangjun Huang, Xianfeng Zhao · 2023 · IEEE Transactions on Multimedia
  32. Sibling-Attack: Rethinking Transferable Adversarial Attacks against Face Recognition
    Zexin Li, Bangjie Yin, Taiping Yao, Junfeng Guo, Shouhong Ding, Simin Chen, Cong Liu · 2023 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  33. Benchmarking Deep Learning Frameworks: Design Considerations, Metrics and Beyond
    Ling Liu, Yanzhao Wu, Wenqi Wei, Wenqi Cao, Semih Şahin, Qi Zhang · 2018 · IEEE International Conference on Distributed Computing Systems (ICDCS)
  34. CD-UAP: Class Discriminative Universal Adversarial Perturbation
    Chaoning Zhang, Philipp Benz, Tooba Imtiaz, In-So Kweon · 2020 · Proceedings of the AAAI Conference on Artificial Intelligence
  35. Adversarial Robustness on In- and Out-Distribution Improves Explainability
    Maximilian Augustin, Alexander Meinke, Matthias Hein · 2020 · Lecture notes in computer science
  36. Decision-based evasion attacks on tree ensemble classifiers
    Fuyong Zhang, Yi Wang, Shigang Liu, Hua Wang · 2020 · World Wide Web
  37. Detection of Face Recognition Adversarial Attacks
    Fabio Valerio Massoli, Fabio Carrara, Giuseppe M. Amato, Fabrizio Falchi · 2020 · Computer Vision and Image Understanding
  38. T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack
    Boxin Wang, Hengzhi Pei, Boyuan Pan, Qian Chen, Shuohang Wang, Bo Li · 2020 · Conference on Empirical Methods in Natural Language Processing (EMNLP)
  39. Cats are not fish
    David Berend, Xiaofei Xie, Lei Ma, Lingjun Zhou, Yang Liu, Chi Xu, Jianjun Zhao · 2020 · IEEE/ACM International Conference on Automated Software Engineering (ASE)
  40. Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions
    Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton · 2019 · arXiv (Cornell University)
  41. Semantic Robustness of Models of Source Code
    Henkel, Jordan, Ramakrishnan, Goutham, Wang, Zi, Albarghouthi, Aws, Jha, Somesh, Reps, Thomas · 2022 · 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)
  42. Tiki-Taka
    Chaoyun Zhang, Xavier Costa‐Pérez, Paul Patras · 2020 · Cloud Computing Security Workshop
  43. A Deep Ensemble-Based Wireless Receiver Architecture for Mitigating Adversarial Attacks in Automatic Modulation Classification
    Rajeev Sahay, Christopher G. Brinton, David J. Love · 2021 · IEEE Transactions on Cognitive Communications and Networking
  44. Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems
    Wei Jia, Zhaojun Lu, Haichun Zhang, Zhenglin Liu, Jie Wang, Gang Qu · 2022 · Network and Distributed System Security Symposium
  45. Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective
    M. H. Meng, Guang-Dong Bai, Sin G. Teo, Zhe Hou, Yan Xiao, Yun Lin, Jin-Song Dong · 2022 · IEEE Transactions on Dependable and Secure Computing
  46. Audio-domain position-independent backdoor attack via unnoticeable triggers
    Cong Shi, Tianfang Zhang, Zhuohang Li, Huy Phan, Tianming Zhao, Yan Wang, Jian Liu, Bo Yuan, Yingying Jennifer Chen · 2022 · ACM Annual International Conference on Mobile Computing and Networking (MobiCom)
  47. Automatic Evasion of Machine Learning-Based Network Intrusion Detection Systems
    Haonan Yan, Xiaoguang Li, Wenjing Zhang, Rui Wang, Hui Li, Xingwen Zhao, Fenghua Li, Xiaodong Lin · 2023 · IEEE Transactions on Dependable and Secure Computing
  48. Defending Against Universal Perturbations With Shared Adversarial Training
    Chaithanya Kumar Mummadi, Thomas Brox, Jan Hendrik Metzen · 2019 · IEEE/CVF International Conference on Computer Vision (ICCV)
  49. Exact Adversarial Attack to Image Captioning via Structured Output Learning With Latent Variables
    Yan Xu, Baoyuan Wu, Fumin Shen, Yanbo Fan, Yong Zhang, Heng Tao Shen, Wei Liu · 2019 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  50. Adaptive iterative attack towards explainable adversarial robustness
    Yucheng Shi, Yahong Han, Quanxin Zhang, Xiaohui Kuang · 2020 · Pattern Recognition
  51. Fault Sneaking Attack
    Pu Zhao, Siyue Wang, Cheng Gongye, Yanzhi Wang, Yunsi Fei, Xue Lin · 2019 · ACM/IEEE Design Automation Conference (DAC)
  52. Dirty Road Can Attack: Security of Deep Learning based Automated Lane Centering under Physical-World Attack
    Takami Sato, Junjie Shen, Ningfei Wang, Jia, Yunhan Jack, Xue Lin, Qi Alfred Chen · 2020 · arXiv (Cornell University)
  53. BayesOpt Adversarial Attack
    Binxin Ru, Adam D. Cobb, Arno Blaas, Yarin Gal · 2020 · International Conference on Learning Representations
  54. Dynamic Time Warping Based Adversarial Framework for Time-Series Domain
    Taha Belkhouja, Yan Yan, Janardhan Rao Doppa · 2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence
  55. Detection of wheat scab fungus spores utilizing the Yolov5-ECA-ASFF network structure
    Dongyan Zhang, Wenhao Zhang, Tao Cheng, Xin‐Gen Zhou, Zihao Yan, Yuhang Wu, Gan Zhang, Xue Yang · 2023 · Computers and Electronics in Agriculture
  56. Physical Adversarial Attacks for Camera-Based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlook
    Amira Guesmi, Muhammad Abdullah Hanif, Bassem Ouni, Muhammad Shafique · 2023 · IEEE Access
  57. A survey of strategy-driven evasion methods for PE malware: Transformation, concealment, and attack
    Jiaxuan Geng, Junfeng Wang, Zhiyang Fang, Yingjie Zhou, Di Jia Wu, Wenhan Ge · 2023 · Computers & Security
  58. On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions
    Yusuke Tsuzuku, Issei Sato · 2019 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  59. Adversarial CAPTCHAs
    Chenghui Shi, Xiaogang Xu, Shouling Ji, Kai Bu, Jianhai Chen, Raheem Beyah, Ting Wang · 2021 · IEEE Transactions on Cybernetics
  60. Hilbert-Based Generative Defense for Adversarial Examples
    Yang Bai, Yan Feng, Yisen Wang, Tao Dai, Shu‐Tao Xia, Yong Jiang · 2019 · IEEE/CVF International Conference on Computer Vision (ICCV)
  61. Imperceptible Misclassification Attack on Deep Learning Accelerator by Glitch Injection
    Wenye Liu, Chip-Hong Chang, Fan Zhang, Xiaoxuan Lou · 2020 · ACM/IEEE Design Automation Conference (DAC)
  62. Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries
    Fnu Suya, Jianfeng Chi, David Evans, Yuan Tian · 2019 · arXiv (Cornell University)
  63. Transferable Perturbations of Deep Feature Distributions
    Nathan Inkawhich, Kevin J Liang, Lawrence Carin, Yiran Chen · 2020 · arXiv (Cornell University)
  64. Watch out! Motion is Blurring the Vision of Your Deep Neural Networks
    Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Jian Wang, Bing Yu, Wei Feng, Yang Liu · 2020 · arXiv (Cornell University)
  65. Targeted Attention Attack on Deep Learning Models in Road Sign Recognition
    Xinghao Yang, Weifeng Liu, Shengli Zhang, Wei Liu, Dacheng Tao · 2020 · IEEE Internet of Things Journal
  66. Distribution-Aware Testing of Neural Networks Using Generative Models
    Swaroopa Dola, Matthew B. Dwyer, Mary Lou Soffa · 2021 · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
  67. Boosting 3D Adversarial Attacks With Attacking on Frequency
    Binbin Liu, Jinlai Zhang, Jihong Zhu · 2022 · IEEE Access
  68. Network intrusion detection system: A survey on artificial intelligence‐based techniques
    Mohammed Sayeeduddin Habeeb, Tummala Ranga Babu · 2022 · Expert Systems
  69. Semantic Adversarial Deep Learning
    Tommaso Dreossi, Somesh Jha, Sanjit Arunkumar Seshia · 2018 · Lecture notes in computer science
  70. A Survey of Game Theoretic Approaches for Adversarial Machine Learning in Cybersecurity Tasks
    Prithviraj Dasgupta, Joseph B. Collins · 2019 · AI Magazine
  71. Improving Adversarial Robustness via Guided Complement Entropy
    Haoyun Chen, Jhao-Hong Liang, Shih-Chieh Chang, Jia-Yu Pan, Yuting Chen, Wei Wei, Da-Cheng Juan · 2019 · IEEE/CVF International Conference on Computer Vision (ICCV)
  72. Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models
    Xiao Zang, Yi Xie, Jie Chen, Bo Yuan · 2021 · International Joint Conference on Artificial Intelligence
  73. Voiceprint Mimicry Attack Towards Speaker Verification System in Smart Home
    Lei Zhang, Yan Meng, Jiahao Yu, Chong Xiang, Brandon Falk, Haojin Zhu · 2020 · IEEE Conference on Computer Communications (INFOCOM)
  74. ES Attack: Model Stealing Against Deep Neural Networks Without Data Hurdles
    Xiaoyong Yuan, Lei Ding, Lan Zhang, Xiaolin Li, Dapeng Oliver Wu · 2022 · IEEE Transactions on Emerging Topics in Computational Intelligence
  75. Adversarial Attacks on Time-Series Intrusion Detection for Industrial Control Systems
    Giulio Zizzo, Chris Hankin, Sergio Maffeis, Kevin Jones · 2020 · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
  76. Deep image prior based defense against adversarial examples
    Tao Dai, Yan Feng, Bin Chen, Jian Jiang Lu, Shu‐Tao Xia · 2021 · Pattern Recognition
  77. Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression
    Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Siwei Li, Li Chen, Michael E. Kounavis, Duen Horng Chau · 2018 · arXiv (Cornell University)
  78. Attack Graph Convolutional Networks by Adding Fake Nodes
    Xiaoyun Wang, Minhao Cheng, Joe Eaton, Cho‐Jui Hsieh, Felix Wu · 2018 · arXiv (Cornell University)
  79. Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing
    Jia, Jinyuan, Xiaoyu Cao, Binghui Wang, Neil Zhenqiang Gong · 2019 · arXiv (Cornell University)
  80. FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments
    Chernikova, Alesia, Oprea, Alina · 2022 · ACM Transactions on Privacy and Security
  81. Understanding the Robustness of Skeleton-based Action Recognition under Adversarial Attack
    He Wang, Feixiang He, Zhexi Peng, Tianjia Shao, Yongliang Yang, Kun Zhou, David Hogg · 2021 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  82. DeepRepair: Style-Guided Repairing for Deep Neural Networks in the Real-World Operational Environment
    Bing Yu, Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Jianjun Zhao · 2021 · IEEE Transactions on Reliability
  83. Generalizable Black-Box Adversarial Attack With Meta Learning
    Fei Yin, Yong Zhang, Baoyuan Wu, Yan Feng, Jingyi Zhang, Yanbo Fan, Yujiu Yang · 2023 · IEEE Transactions on Pattern Analysis and Machine Intelligence
  84. A Survey on Learning to Reject
    Xu-Yao Zhang, Guo-Sen Xie, Xiu-Chuan Li, T. Mei, Cheng-Lin Liu · 2023 · Proceedings of the IEEE
  85. Trustworthy artificial intelligence in Alzheimer’s disease: state of the art, opportunities, and challenges
    Shaker El–Sappagh, José M. Alonso, Tamer Abuhmed, Farman Ali, Alberto Bugarín · 2023 · Artificial Intelligence Review
  86. Study of Pre-Processing Defenses Against Adversarial Attacks on State-of-the-Art Speaker Recognition Systems
    Joshi, Sonal, Villalba, Jesus, Zelasko, Piotr, Moro-Velazquez, Laureano, Dehak, Najim · 2021 · IEEE Transactions on Information Forensics and Security
  87. Machine Learning for Health: Algorithm Auditing & Quality Control
    Oala, Luis, Murchison, Andrew G., Balachandran, Pradeep, Choudhary, Shruti, Fehr, Jana, Leite, Alixandro Werneck, Goldschmidt, Peter G., Johner, Christian, Schörverth, Elora D. M., Nakasi, Rose et al. · 2021 · Journal of Medical Systems
  88. Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach
    Bayram, Firas, Ahmed, Bestoun S. · 2025 · ACM Computing Surveys
  89. Residual error based knowledge distillation
    Gao, Mengya, Wang, Yujun, Wan, Liang · 2021 · Neurocomputing
  90. The Challenges and Opportunities of Artificial Intelligence for Trustworthy Robots and Autonomous Systems
    He, Hongmei, Gray, John, Cangelosi, Angelo, Meng, Qinggang, McGinnity, T. M., Mehnen, Jorn · 2020 · 2020 3rd International Conference on Intelligent Robotic and Control Engineering (IRCE)
  91. Text Backdoor Detection Using an Interpretable RNN Abstract Model
    Fan, Ming, Si, Ziliang, Xie, Xiaofei, Liu, Yang, Liu, Ting · 2021 · IEEE Transactions on Information Forensics and Security
  92. Learning to Control in Power Systems: Design and Analysis Guidelines for Concrete Safety Problems
    Dobbe, Roel, Hidalgo-Gonzalez, Patricia, Karagiannopoulos, Stavros, Henriquez-Auba, Rodrigo, Hug, Gabriela, Callaway, Duncan S., Tomlin, Claire J. · 2020 · Electric Power Systems Research
  93. Comprehensive Evaluation of Deepfake Detection Models: Accuracy, Generalization, and Resilience to Adversarial Attacks
    Abbasi, Maryam, Váz, Paulo, Silva, José, Martins, Pedro · 2025 · Applied Sciences
  94. Encryption Inspired Adversarial Defense For Visual Classification
    Maung, Maung, Pyone, April, Kiya, Hitoshi · 2020 · 2020 IEEE International Conference on Image Processing (ICIP)
  95. Dispersed Pixel Perturbation-Based Imperceptible Backdoor Trigger for Image Classifier Models
    Wang, Yulong, Zhao, Minghui, Li, Shenghong, Yuan, Xin, Ni, Wei · 2022 · IEEE Transactions on Information Forensics and Security
  96. CUDA: Convolution-Based Unlearnable Datasets
    Sadasivan, Vinu Sankar, Soltanolkotabi, Mahdi, Feizi, Soheil · 2023 · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  97. Is Multi-Modal Necessarily Better? Robustness Evaluation of Multi-Modal Fake News Detection
    Chen, Jinyin, Jia, Chengyu, Zheng, Haibin, Chen, Ruoxi, Fu, Chenbo · 2023 · IEEE Transactions on Network Science and Engineering
  98. Mitigating Adversarial Attacks in Federated Learning with Trusted Execution Environments
    Queyrut, Simon, Schiavoni, Valerio, Felber, Pascal · 2023 · 2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS)
  99. Stratification by Tumor Grade Groups in a Holistic Evaluation of Machine Learning for Brain Tumor Segmentation
    Prabhudesai, Snehal, Wang, Nicholas Chandler, Ahluwalia, Vinayak, Huan, Xun, Bapuraj, Jayapalli Rajiv, Banovic, Nikola, Rao, Arvind · 2021 · Frontiers in Neuroscience
  100. Exploring the Robustness of In-Context Learning with Noisy Labels
    Cheng, Chen, Yu, Xinzhi, Wen, Haodong, Sun, Jingsong, Yue, Guanzhang, Zhang, Yihao, Wei, Zeming · 2025 · ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)