Papers by Ramesh Inturi

1 papers
Word Embedding Binarization with Semantic Information Preservation (2020.coling-main)

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Challenge: Word and Sentence embeddings are one of the most common starting points of any NLP task.
Approach: They propose a way to convert word embedding to binary representation to reduce overall size . they propose different approaches suitable for different downstream tasks based on contextual and semantic information.
Outcome: The proposed method reduces the size of the embedding while keeping the semantic and relational knowledge intact.

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