4 citations · 5 across the 5 of their papers we have counts for
6 papers
A Prompting-based Approach for Adversarial Example Generation and Robustness Enhancement
Yuting Yang, Pei Huang, Juan Cao +5
Recent years have seen the wide application of NLP models in crucial areas such as finance, medical treatment, and news media, raising concerns of the model robustness and vulnerab…
Quantifying Robustness to Adversarial Word Substitutions
Yuting Yang, Pei Huang, FeiFei Ma +4
Deep-learning-based NLP models are found to be vulnerable to word substitution perturbations. Before they are widely adopted, the fundamental issues of robustness need to be addres…
ε-weakened Robustness of Deep Neural Networks
Pei Huang, Yuting Yang, Minghao Liu +3
This paper introduces a notation of -weakened robustness for analyzing the reliability and stability of deep neural networks (DNNs). Unlike the conventional robustness…
On the Fixed-Parameter Tractability of Some Matching Problems Under the Color-Spanning Model
Sergey Bereg, Feifei Ma, Wencheng Wang +2
Given a set of points in the plane, each colored with one of the given colors, a color-spanning set is a subset of points with distinct colors. The min…
A New Probabilistic Algorithm for Approximate Model Counting
Cunjing Ge, Feifei Ma, Tian Liu +1
Constrained counting is important in domains ranging from artificial intelligence to software analysis. There are already a few approaches for counting models over various types of…
A Tool for Computing and Estimating the Volume of the Solution Space of SMT(LA)
Cunjing Ge, Feifei Ma, Jian Zhang
There are already quite a few tools for solving the Satisfiability Modulo Theories (SMT) problems. In this paper, we present \texttt{VolCE}, a tool for counting the solutions of SM…