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Found 6 papers, 1 papers with code
On the Transferability of Adversarial Attacks against Neural Text Classifier
Based on these studies, we propose a genetic algorithm to find an ensemble of models that can be used to induce adversarial examples to fool almost all existing models.
Boximator: Generating Rich and Controllable Motions for Video Synthesis
Its robust motion controllability is validated by drastic increases in the bounding box alignment metric.
Certified Robustness to Text Adversarial Attacks by Randomized [MASK]
Recently, few certified defense methods have been developed to provably guarantee the robustness of a text classifier to adversarial synonym substitutions.
Alleviate Exposure Bias in Sequence Prediction \\ with Recurrent Neural Networks
The key idea is that at each time step, the network takes as input a ``bundle'' of similar words predicted at the previous step instead of a single ground truth.
SparseGAN: Sparse Generative Adversarial Network for Text Generation
It is still a challenging task to learn a neural text generation model under the framework of generative adversarial networks (GANs) since the entire training process is not differentiable.
On the Transferability of Adversarial Attacksagainst Neural Text Classifier
Based on these studies, we propose a genetic algorithm to find an ensemble of models that can be used to induce adversarial examples to fool almost all existing models.
