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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.
In Excel and Word 95 and prior editions a weak protection algorithm is used that converts a password to a 16-bit verifier and a 16-byte XOR obfuscation array [1] key. [4] Hacking software is now readily available to find a 16-byte key and decrypt the password-protected document. [5] Office 97, 2000, XP and 2003 use RC4 with 40 bits. [4]
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 ]
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.
fastText is a library for learning of word embeddings and text classification created by Facebook's AI Research (FAIR) lab. [3] [4] [5] [6] The model allows one to ...