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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]
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.
High-level schematic diagram of BERT. It takes in a text, tokenizes it into a sequence of tokens, add in optional special tokens, and apply a Transformer encoder. The hidden states of the last layer can then be used as contextual word embeddings. BERT is an "encoder-only" transformer architecture. At a high level, BERT consists of 4 modules:
In spoken language, multiple center-embeddings even of degree 2 are so rare as to be practically non-existing. [ 1 ] Center embedding is the focus of a science fiction novel, Ian Watson 's The Embedding , and plays a part in Ted Chiang 's Story of Your Life .
Textual entailment measures natural language understanding as it asks for a semantic interpretation of the text, and due to its generality remains an active area of research. Many approaches and refinements of approaches have been considered, such as word embedding , logical models, graphical models, rule systems, contextual focusing, and ...
An "encoder-only" Transformer applies the encoder to map an input text into a sequence of vectors that represent the input text. This is usually used for text embedding and representation learning for downstream applications. BERT is encoder-only. They are less often used currently, as they were found to be not significantly better than ...
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 ...
Readability is the ease with which a reader can understand a written text.The concept exists in both natural language and programming languages though in different forms. In natural language, the readability of text depends on its content (the complexity of its vocabulary and syntax) and its presentation (such as typographic aspects that affect legibility, like font size, line height ...