Adaptive Metric

Adaptive metrics are methods designed to dynamically adjust evaluation criteria or model parameters based on the specific context or data at hand, aiming to improve performance and robustness across diverse situations. Current research focuses on developing adaptive metrics for various applications, including optimizing data acquisition in medical imaging, enhancing the resilience of neural networks against adversarial attacks, and improving the efficiency and generalizability of large language models and depth estimation algorithms. These advancements are significant because they address limitations of traditional fixed metrics, leading to more accurate, efficient, and reliable systems across diverse domains.