This AI Paper Introduces Sub-Sentence Encoder: A Contrastively-Learned Contextual Embedding AI Model for Fine-Grained Semantic Representation of Text

Researchers from the University of Pennsylvania, the University of Washington, and Tencent AI Lab propose a sub-sentence encoder, a contrastively learned contextual embedding model that generates distinct embeddings for atomic propositions within a text sequence. Unlike traditional sentence embeddings, it focuses on fine-grained semantic representation by learning contextual embeddings for different units of meaning. The […]

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