Sentence Transformer

Sentence transformers are language models designed to generate semantically meaningful vector representations of sentences, enabling efficient semantic search and comparison. Current research focuses on improving their performance in low-resource settings, adapting them to specialized domains (e.g., aviation, legal text), and integrating them with other techniques like large language models and dimensionality reduction methods to enhance speed and accuracy for tasks such as intent detection, stance detection, and relation prediction. This work is significant because sentence transformers are proving valuable in various applications, including question answering, risk assessment, and automated auditing, particularly where labeled data is scarce or domain expertise is crucial.