Sentence Representation

Sentence representation focuses on encoding the meaning of sentences into numerical vectors, enabling computers to understand and process natural language. Current research emphasizes improving the quality of these representations through techniques like contrastive learning, which learns by comparing sentence pairs, and incorporating both sentence-level and token-level information for more nuanced understanding. This field is crucial for advancements in various NLP tasks, including semantic similarity assessment, text summarization, and question answering, impacting both scientific understanding of language and the development of practical applications.