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OverviewNeural language models are probabilistic models of text parameterized by neural networks. They are widely applicable to applications with outputs consisting of discrete sequences, such as document summarization, question answering, and image captioning. The minimal assumptions about data enable advancements in language modeling to drive improvements across a diverse array of applications. In natural language, structures are both pervasive and essential. For example, a book is organized into chapters, with a logical flow connecting them; without this structure, the book would lose its coherence. Therefore, effectively understanding and modeling textual sequences requires comprehending and representing the inherent structures. This thesis focuses on structure modeling for language models. Full Product DetailsAuthor: Mary R BuchananPublisher: Priya Publishers Imprint: Priya Publishers Dimensions: Width: 15.20cm , Height: 0.60cm , Length: 22.90cm Weight: 0.159kg ISBN: 9782157619441ISBN 10: 2157619445 Pages: 112 Publication Date: 26 September 2023 Audience: General/trade , General Format: Paperback Publisher's Status: Active Availability: In stock  We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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