Sparse Autoencoders (SAEs) have recently gained attention as a means to improve the interpretability and steerability of Large Language Models (LLMs), both of which are essential for AI safety. In ...

Abstract: Deep learning models in computer vision face challenges such as high computational resource demands and limited generalization in practical scenarios. To address these issues, this study ...

Abstract: Object measurement in images is crucial in computer vision, with applications in industrial automation, quality control, and medical imaging. Traditional manual methods are inefficient and ...