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Each attention head learns different linear projections of the Q, K, and V matrices. This allows the model to capture different aspects of the relationships between words in the sequence simultaneously, rather than focusing on a single aspect. By doing this, multi-head attention ensures that the input embeddings are updated from a more varied ...
Many transformer attention heads encode relevance relations that are meaningful to humans. For example, some attention heads can attend mostly to the next word, while others mainly attend from verbs to their direct objects. [56] The computations for each attention head can be performed in parallel, which allows for
Bahdanau-style attention, [41] also referred to as additive attention, Luong-style attention, [42] which is known as multiplicative attention, highly parallelizable self-attention introduced in 2016 as decomposable attention [31] and successfully used in transformers a year later, positional attention and factorized positional attention. [43]
Operating on byte-sized tokens, transformers scale poorly as every token must "attend" to every other token leading to O(n 2) scaling laws, as a result, Transformers opt to use subword tokenization to reduce the number of tokens in text, however, this leads to very large vocabulary tables and word embeddings.
The Swin Transformer ("Shifted windows") [13] took inspiration from standard CNNs: Instead of performing self-attention over the entire sequence of tokens, one for each patch, it performs "shifted window based" self-attention, which means only performing attention over square-shaped blocks of patches.
The text encoding models used in CLIP are typically Transformers. In the original OpenAI report, they reported using a Transformer (63M-parameter, 12-layer, 512-wide, 8 attention heads) with lower-cased byte pair encoding (BPE) with 49152 vocabulary size. Context length was capped at 76 for efficiency.
The Center for Accessible Technology, formerly the Disabled Children's Computer Group (DCCG), was started in 1983 [1] in El Cerrito, California, by several parents, educators, and assistive technology developers who felt that the new computer technology could assist children and adults with disabilities to speak, write, read, learn, and participate in a larger world.
The concept of DAMP (deficits in attention, motor control, and perception) has been in clinical use in Scandinavia for about 20 years. DAMP is diagnosed on the basis of concomitant attention deficit/hyperactivity disorder and developmental coordination disorder in children who do not have a severe learning disability or cerebral palsy.