| Display title | Attention (machine learning) |
| Default sort key | Attention (machine learning) |
| Page length (in bytes) | 26,751 |
| Namespace ID | 0 |
| Page ID | 327398 |
| Page content language | en - English |
| Page content model | wikitext |
| Indexing by robots | Allowed |
| Number of redirects to this page | 0 |
| Counted as a content page | Yes |
| Page image |  |
| HandWiki item ID | None |
| Edit | Allow all users (infinite) |
| Move | Allow all users (infinite) |
| Page creator | imported>Steve2012 |
| Date of page creation | 22:05, 8 February 2024 |
| Latest editor | imported>Steve2012 |
| Date of latest edit | 22:05, 8 February 2024 |
| Total number of edits | 1 |
| Recent number of edits (within past 90 days) | 0 |
| Recent number of distinct authors | 0 |
Description | Content |
Article description: (description)
This attribute controls the content of the description and og:description elements. | Machine learning-based attention is a mechanism which intuitively mimicks cognitive attention. It calculates "soft" weights for each word, more precisely for its embedding, in the context window. These weights can be computed either in parallel (such as in transformers) or sequentially (such as recurrent... |
