5 papers
Neural-guided, Bidirectional Program Search for Abstraction and Reasoning
Simon Alford, Anshula Gandhi, Akshay Rangamani +6
One of the challenges facing artificial intelligence research today is designing systems capable of utilizing systematic reasoning to generalize to new tasks. The Abstraction and R…
Application of Seq2Seq Models on Code Correction
Shan Huang, Xiao Zhou, Sang Chin
We apply various seq2seq models on programming language correction tasks on Juliet Test Suite for C/C++ and Java of Software Assurance Reference Datasets(SARD), and achieve 75\%(fo…
Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses
Xiao Wang, Siyue Wang, Pin-Yu Chen +4
Despite achieving remarkable success in various domains, recent studies have uncovered the vulnerability of deep neural networks to adversarial perturbations, creating concerns on…
NodeDrop: A Condition for Reducing Network Size without Effect on Output
Louis Jensen, Jacob Harer, Sang Chin
Determining an appropriate number of features for each layer in a neural network is an important and difficult task. This task is especially important in applications on systems wi…
Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks
Siyue Wang, Xiao Wang, Pu Zhao +4
Deep neural networks (DNNs) are known vulnerable to adversarial attacks. That is, adversarial examples, obtained by adding delicately crafted distortions onto original legal inputs…