Researchers designed Phase Attacks to target the phase information of complex-valued neural networks, which are gaining popularity. They also derived complex-valued versions of common adversarial attacks. The study shows that CVNNs are more robust in some scenarios but still vulnerable to phase changes, highlighting the need for robustness analysis in AI model development.