Semantic Prototype

Semantic prototypes represent the core characteristics of data clusters, aiming to improve the explainability and interpretability of complex machine learning models. Current research focuses on developing methods that generate more accurate and informative prototypes, often leveraging semantic descriptions and visual augmentation to enhance their representational power within various learning paradigms, including zero-shot and few-shot learning, and relation extraction. This work is significant because it addresses the "black box" nature of many ML models, fostering trust and enabling more effective human-computer interaction in diverse applications such as image recognition and knowledge graph completion.