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In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis . Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [ 1 ]
Object Linking and Embedding (OLE) is a proprietary technology developed by Microsoft that allows embedding and linking to documents and other objects. For developers, it brought OLE Control Extension (OCX), a way to develop and use custom user interface elements.
Indenting text this is used when replying on a talk page , to make it easier to follow conversations. After a string of indents, or to revive a discussion, an outdent {{Outdent|n}} ( Template:Outdent ) can be used to reset the paragraph to the left margin.
Font embedding is the inclusion of font files inside an electronic document for display across different platforms. Font embedding is controversial because it allows licensed fonts to be freely distributed.
the hidden size and embedding size are synonymous. Both of them denote the number of real numbers used to represent a token. Both of them denote the number of real numbers used to represent a token. The notation for encoder stack is written as L/H.
The reasons for successful word embedding learning in the word2vec framework are poorly understood. Goldberg and Levy point out that the word2vec objective function causes words that occur in similar contexts to have similar embeddings (as measured by cosine similarity) and note that this is in line with J. R. Firth's distributional hypothesis ...
In practice however, BERT's sentence embedding with the [CLS] token achieves poor performance, often worse than simply averaging non-contextual word embeddings. SBERT later achieved superior sentence embedding performance [8] by fine tuning BERT's [CLS] token embeddings through the usage of a siamese neural network architecture on the SNLI dataset.
An embedding, or a smooth embedding, is defined to be an immersion that is an embedding in the topological sense mentioned above (i.e. homeomorphism onto its image). [ 4 ] In other words, the domain of an embedding is diffeomorphic to its image, and in particular the image of an embedding must be a submanifold .