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Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...
RightArc (current token is the parent of the top of the stack, replaces top) Shift (add current token to the stack) The algorithm can be formulated as comparing the top two tokens of the stack (after adding the next token to the stack) or the top token on the stack and the next token in the sentence.
Selection bias refers the inherent tendency of large language models to favor certain option identifiers irrespective of the actual content of the options. This bias primarily stems from token bias—that is, the model assigns a higher a priori probability to specific answer tokens (such as “A”) when generating responses.
As of 2020, BERT is a ubiquitous baseline in natural language processing (NLP) experiments. [3] BERT is trained by masked token prediction and next sentence prediction. As a result of this training process, BERT learns contextual, latent representations of tokens in their context, similar to ELMo and GPT-2. [4]
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
A lexical token is a string with an assigned and thus identified meaning, in contrast to the probabilistic token used in large language models. A lexical token consists of a token name and an optional token value. The token name is a category of a rule-based lexical unit. [2]
n-gram – sequence of n number of tokens, where a "token" is a character, syllable, or word. The n is replaced by a number. Therefore, a 5-gram is an n-gram of 5 letters, syllables, or words. "Eat this" is a 2-gram (also known as a bigram). Bigram – n-gram of 2 tokens. Every sequence of 2 adjacent elements in a string of tokens is a bigram.
For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...