Semantic Unit

Semantic units represent the smallest meaningful components of language, encompassing words, phrases, or even sub-word units depending on the context and application. Current research focuses on identifying and leveraging these units within various language processing tasks, employing techniques like self-supervised learning to create coarse semantic representations for speech and rank-wise clustering to merge and manipulate parameters in large language models. This work aims to improve model efficiency, address limitations like the "reversal curse," and enhance performance in areas such as machine translation and speech recognition, ultimately leading to more robust and nuanced natural language understanding.