43 citations · 47 across the 4 of their papers we have counts for
5 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…
Generalizing Neural Networks by Reflecting Deviating Data in Production
Yan Xiao, Yun Lin, Ivan Beschastnikh +3
Trained with a sufficiently large training and testing dataset, Deep Neural Networks (DNNs) are expected to generalize. However, inputs may deviate from the training dataset distri…
Self-Checking Deep Neural Networks in Deployment
Yan Xiao, Ivan Beschastnikh, David S. Rosenblum +4
The widespread adoption of Deep Neural Networks (DNNs) in important domains raises questions about the trustworthiness of DNN outputs. Even a highly accurate DNN will make mistakes…
CoinWatch: A Clone-Based Approach For Detecting Vulnerabilities in Cryptocurrencies
Qingze Hum, Wei Jin Tan, Shi Ying Tey +4
Cryptocurrencies have become very popular in recent years. Thousands of new cryptocurrencies have emerged, proposing new and novel techniques that improve on Bitcoin's core innovat…
sFuzz: An Efficient Adaptive Fuzzer for Solidity Smart Contracts
Tai D. Nguyen, Long H. Pham, Jun Sun +2
Smart contracts are Turing-complete programs that execute on the infrastructure of the blockchain, which often manage valuable digital assets. Solidity is one of the most popular p…