Introduction Data deduplication for model training refers to the process of identifying and removing duplicate or near-duplicate data from datasets used to train machine learning and AI models. This includes exact duplicates, semantic duplicates, and near-identical samples across text, images, audio, and multimodal datasets. deduplication has become a critical step in AI pipelines because large-scale Read More