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For example, a prompt may include a few examples for a model to learn from, such as asking the model to complete "maison → house, chat → cat, chien →" (the expected response being dog), [23] an approach called few-shot learning. [24] In-context learning is an emergent ability [25] of large language models.
Few-shot learning and one-shot learning may refer to: Few-shot learning, a form of prompt engineering in generative AI; One-shot learning (computer vision)
One-shot learning is an object categorization problem, found mostly in computer vision. Whereas most machine learning -based object categorization algorithms require training on hundreds or thousands of examples, one-shot learning aims to classify objects from one, or only a few, examples.
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However, the use of a real time ticking bomb through the single shot is seen as a standard. [2] Although animated films are not included in a list of one-shot films, The Wolf House (2018) is a deconstructed example of (stop-motion) animated film that presented in a form of single, unbroken shot sequence. [5] [6] [7]
In comics, a one-shot is a work composed of a single standalone issue or chapter, contrasting a limited series or ongoing series, which are composed of multiple issues or chapters. [1] One-shots date back to the early 19th century, published in newspapers, and today may be in the form of single published comic books , parts of comic magazines ...
No one's sure exactly why this woman had a story to tell, because this woman lived as many as 6,000 years ago. We can still imagine her intoning scary scenes with foreign howls. A charming man's buttery voice might've won over a reluctant, longhaired princess; a beguiling forest creature's dry cackle a smoke signal for danger.