Search Results for author: Mirazul Haque

Found 9 papers, 2 papers with code

TestAug: A Framework for Augmenting Capability-based NLP Tests

1 code implementation COLING 2022 Guanqun Yang, Mirazul Haque, Qiaochu Song, Wei Yang, Xueqing Liu

Our experiments show that TestAug has three advantages over the existing work on behavioral testing: (1) TestAug can find more bugs than existing work; (2) The test cases in TestAug are more diverse; and (3) TestAug largely saves the manual efforts in creating the test suites.

DeepPerform: An Efficient Approach for Performance Testing of Resource-Constrained Neural Networks

no code implementations10 Oct 2022 Simin Chen, Mirazul Haque, Cong Liu, Wei Yang

To ensure an AdNN satisfies the performance requirements of resource-constrained applications, it is essential to conduct performance testing to detect IDPBs in the AdNN.

CorrGAN: Input Transformation Technique Against Natural Corruptions

no code implementations19 Apr 2022 Mirazul Haque, Christof J. Budnik, Wei Yang

These DNNs are vulnerable to adversarial perturbations and corruptions.

NICGSlowDown: Evaluating the Efficiency Robustness of Neural Image Caption Generation Models

1 code implementation CVPR 2022 Simin Chen, Zihe Song, Mirazul Haque, Cong Liu, Wei Yang

To further understand such efficiency-oriented threats, we propose a new attack approach, NICGSlowDown, to evaluate the efficiency robustness of NICG models.

EREBA: Black-box Energy Testing of Adaptive Neural Networks

no code implementations12 Feb 2022 Mirazul Haque, Yaswanth Yadlapalli, Wei Yang, Cong Liu

The test inputs generated by EREBA can increase the energy consumption of AdNNs by 2, 000% compared to the original inputs.

TransSlowDown: Efficiency Attacks on Neural Machine Translation Systems

no code implementations29 Sep 2021 Simin Chen, Mirazul Haque, Zihe Song, Cong Liu, Wei Yang

To further the understanding of such efficiency-oriented threats and raise the community’s concern on the efficiency robustness of NMT systems, we propose a new attack approach, TranSlowDown, to test the efficiency robustness of NMT systems.

Machine Translation NMT +1

NODEAttack: Adversarial Attack on the Energy Consumption of Neural ODEs

no code implementations29 Sep 2021 Mirazul Haque, Simin Chen, Wasif Arman Haque, Cong Liu, Wei Yang

Unlike the memory cost, the energy consumption of the Neural ODEs during inference can be adaptive because of the adaptive nature of the ODE solvers.

Adversarial Attack Object Recognition

ILFO: Adversarial Attack on Adaptive Neural Networks

no code implementations CVPR 2020 Mirazul Haque, Anki Chauhan, Cong Liu, Wei Yang

With the increasing number of layers and parameters in neural networks, the energy consumption of neural networks has become a great concern to society, especially to users of handheld or embedded devices.

Adversarial Attack

Cannot find the paper you are looking for? You can Submit a new open access paper.