8 citations · 13 across the 4 of their papers we have counts for
5 papers
Finding Friends and Flipping Frenemies: Automatic Paraphrase Dataset Augmentation Using Graph Theory
Hannah Chen, Yangfeng Ji, David Evans
Most NLP datasets are manually labeled, so suffer from inconsistent labeling or limited size. We propose methods for automatically improving datasets by viewing them as graphs with…
Pointwise Paraphrase Appraisal is Potentially Problematic
Hannah Chen, Yangfeng Ji, David Evans
The prevailing approach for training and evaluating paraphrase identification models is constructed as a binary classification problem: the model is given a pair of sentences, and…
Revisiting Membership Inference Under Realistic Assumptions
Bargav Jayaraman, Lingxiao Wang, Katherine Knipmeyer +2
We study membership inference in settings where some of the assumptions typically used in previous research are relaxed. First, we consider skewed priors, to cover cases such as wh…
Certifying Joint Adversarial Robustness for Model Ensembles
Mainuddin Ahmad Jonas, David Evans
Deep Neural Networks (DNNs) are often vulnerable to adversarial examples.Several proposed defenses deploy an ensemble of models with the hope that, although the individual models m…
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization
Sicheng Zhu, Xiao Zhang, David Evans
Training machine learning models that are robust against adversarial inputs poses seemingly insurmountable challenges. To better understand adversarial robustness, we consider the…