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t. e. A standard Transformer architecture, showing on the left an encoder, and on the right a decoder. Note: it uses the pre-LN convention, which is different from the post-LN convention used in the original 2017 Transformer. A transformer is a deep learning architecture developed by researchers at Google and based on the multi-head attention ...
Attention is a machine learning method that determines the relative importance of each component in a sequence relative to the other components in that sequence. In natural language processing, importance is represented by "soft" weights assigned to each word in a sentence. More generally, attention encodes vectors called token embeddings ...
An illustration of main components of the transformer model from the paper. " Attention Is All You Need " [1] is a 2017 landmark [2][3] research paper in machine learning authored by eight scientists working at Google. The paper introduced a new deep learning architecture known as the transformer, based on the attention mechanism proposed in ...
BERT (language model) Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. [1][2] It learned by self-supervised learning to represent text as a sequence of vectors. It had the transformer encoder architecture. It was notable for its dramatic improvement over ...
The Bayley Scales of Infant and Toddler Development (version 4 was released September 2019) is a standard series of measurements originally developed by psychologist Nancy Bayley used primarily to assess the development of infants and toddlers, ages 1–42 months. [1] This measure consists of a series of developmental play tasks and takes ...
T5 encoder-decoder structure, showing the attention structure. In the encoder self-attention (lower square), all input tokens attend to each other; In the encoder–decoder cross-attention (upper rectangle), each target token attends to all input tokens; In the decoder self-attention (upper triangle), each target token attends to present and past target tokens only (causal).
Attentional control, colloquially referred to as concentration, refers to an individual's capacity to choose what they pay attention to and what they ignore. [1] It is also known as endogenous attention or executive attention. In lay terms, attentional control can be described as an individual's ability to concentrate.
Constructive developmental framework. The constructive developmental framework (CDF) is a theoretical framework for epistemological and psychological assessment of adults. The framework is based on empirical developmental research showing that an individual's perception of reality is an actively constructed "world of their own", unique to them ...