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Cross-Lingual Word Embedding is a technique that maps words from multiple languages into a Shared vector space, enabling Comparative linguistic analysis and Zero-shot Learning across languages. This approach facilitates applications like Machine Translation and Multilingual Information Retrieval by leveraging the Semantic Relationship between Words across different languages.
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