In just a few years, large language models (LLMs) have expanded from millions to hundreds of billions of parameters, ...

Abstract: Among various few-shot learning methods, metric learning approaches based on local feature representation of images have achieved remarkable results. However, most of these methods coarsely ...

Abstract: Confidence calibration in classification models is a vital technique for accurately estimating the posterior probabilities of predicted results, which is crucial for assessing the likelihood ...