Phantom Threat

"Phantom" refers to a range of research efforts addressing the challenges of unseen or unexpected factors impacting various systems. Current research focuses on detecting and mitigating these "phantom" threats in diverse areas, including autonomous driving (LiDAR attacks), surgical skill assessment (simulated environments), and large language models (adversarial attacks and bias). These studies utilize various techniques, such as novel convolutional neural networks, reinforcement learning frameworks, and prompt engineering, to improve robustness, accuracy, and security across different applications. The overall significance lies in enhancing the reliability and safety of complex systems by identifying and addressing vulnerabilities previously hidden or overlooked.