9 citations · 10 across the 2 of their papers we have counts for
3 papers
cs.LO2022★ 1 cited
Hybrid Inlining: A Compositional and Context Sensitive Static Analysis Framework
Jiangchao Liu, Jierui Liu, Peng Di +4
Context sensitivity is essential for achieving the precision in inter-procedural static analysis. To be (fully) context sensitive, top-down analysis needs to fully inline all state…
cs.LG2020★ 9 cited
Input Validation for Neural Networks via Runtime Local Robustness Verification
Jiangchao Liu, Liqian Chen, Antoine Mine +1
Local robustness verification can verify that a neural network is robust wrt. any perturbation to a specific input within a certain distance. We call this distance Robustness Radiu…
cs.LG2019
Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification
Jianlin Li, Pengfei Yang, Jiangchao Liu +3
Deep neural networks (DNNs) have been shown lack of robustness for the vulnerability of their classification to small perturbations on the inputs. This has led to safety concerns o…