1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.AI2026★ 1 cited
Precise Verification of Transformers through ReLU-Catalyzed Abstraction Refinement
Hengjie Liu, Zhenya Zhang, Jianjun Zhao
Formal verification of transformers has become increasingly important due to their widespread deployment in safety-critical applications. Compared to classic neural networks, the i…
cs.LG2025
Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees
Guanqin Zhang, Kota Fukuda, Zhenya Zhang +4
The vulnerability of neural networks to adversarial perturbations has necessitated formal verification techniques that can rigorously certify the quality of neural networks. As the…
cs.LG2025
Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification
Kota Fukuda, Guanqin Zhang, Zhenya Zhang +2
Formal verification is a rigorous approach that can provably ensure the quality of neural networks, and to date, Branch and Bound (BaB) is the state-of-the-art that performs verifi…