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07/04/2022
Hessian-Free Second-Order Adversarial Examples for Adversarial Learning
Recent studies show deep neural networks (DNNs) are extremely vulnerable...
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04/28/2022
Improving robustness of language models from a geometry-aware perspective
Recent studies have found that removing the norm-bounded projection and ...
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11/12/2021
One model Packs Thousands of Items with Recurrent Conditional Query Learning
Recent studies have revealed that neural combinatorial optimization (NCO...
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09/13/2021
TREATED:Towards Universal Defense against Textual Adversarial Attacks
Recent work shows that deep neural networks are vulnerable to adversaria...
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08/13/2021
CODEs: Chamfer Out-of-Distribution Examples against Overconfidence Issue
Overconfident predictions on out-of-distribution (OOD) samples is a thor...
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02/01/2021
Towards Speeding up Adversarial Training in Latent Spaces
Adversarial training is wildly considered as the most effective way to d...
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12/02/2020
Towards Imperceptible Adversarial Image Patches Based on Network Explanations
The vulnerability of deep neural networks (DNNs) for adversarial example...
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09/19/2020
EI-MTD:Moving Target Defense for Edge Intelligence against Adversarial Attacks
With the boom of edge intelligence, its vulnerability to adversarial att...
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07/31/2020
TEAM: We Need More Powerful Adversarial Examples for DNNs
Although deep neural networks (DNNs) have achieved success in many appli...
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11/27/2019
Decision Propagation Networks for Image Classification
High-level (e.g., semantic) features encoded in the latter layers of con...
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06/30/2018
