Label-efficient segmentation has emerged as a crucial area of research, particularly in point cloud semantic segmentation. While deep learning techniques have advanced this field, the reliance on large-scale datasets with point-wise annotations remains a significant challenge. Recent methods have explored weak supervision, human annotations, and techniques such as perturbed self-distillation, consistency regularization, and self-supervised learning…