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  2. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    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]

  3. Sentence embedding - Wikipedia

    en.wikipedia.org/wiki/Sentence_embedding

    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.

  4. Font embedding - Wikipedia

    en.wikipedia.org/wiki/Font_embedding

    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.

  5. Ada Semantic Interface Specification - Wikipedia

    en.wikipedia.org/wiki/Ada_Semantic_Interface...

    Ada Semantic Interphase Specification under the ISO/IEC 8652 Ada 95 Reference Manual (Ada Language Referencing Manual, 1994) is defined as an interface amidst an Aria environment and other tools requiring information from the Aria environment. Features of ASIS based tools could include: [4] high quality code analysis; automated code monitors ...

  6. Embedding - Wikipedia

    en.wikipedia.org/wiki/Embedding

    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 .

  7. GPT-3 - Wikipedia

    en.wikipedia.org/wiki/GPT-3

    Similar capabilities to text-davinci-003 but trained with supervised fine-tuning instead of reinforcement learning GPT-3.5 text-davinci-003 Undisclosed Can do any language task with better quality, longer output, and consistent instruction-following than the curie, babbage, or ada models. Also supports inserting completions within text. GPT-3.5

  8. Bag-of-words model - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model

    The bag-of-words model (BoW) is a model of text which uses an unordered collection (a "bag") of words. It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity .

  9. eRuby - Wikipedia

    en.wikipedia.org/wiki/ERuby

    Embedded Ruby (also shortened as ERB) is a templating system that embeds Ruby into a text document. It is often used to embed Ruby code in an HTML document, similar to ASP and JSP , and PHP and other server-side scripting languages.