Quadruplet Loss

Quadruplet loss, an extension of triplet loss, is a deep learning technique used to improve the quality of learned embeddings by emphasizing relative distances between data points. Current research focuses on applying quadruplet (and related polytuplet) loss to diverse tasks, including robust face recognition, dimensionality reduction of biological data, cross-modal retrieval, and improving reading comprehension models. These applications highlight the method's versatility in enhancing model performance by focusing on preserving structural relationships within data, leading to improved accuracy and robustness in various domains.