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See a monthly parameter usage report for Template:AI-generated in articles based on its TemplateData. TemplateData for AI-generated This tag is intended to identify articles that need extensive examination because they appear to have been generated using a large language model without rigorous scrutiny.
The category should be renamed from "Articles containing suspected AI-generated texts" to "Articles containing non-compliant AI-generated texts", or perhaps "suspected non-compliant", to make it clear that this is a cleanup category rather than a general category for all articles where LLMs were used (though I suppose there is yet no affirmative consensus on whether LLM text generation is ...
See a monthly parameter usage report for Template:AI-generated in articles based on its TemplateData. TemplateData for AI-generated This tag is intended to identify articles that need extensive examination because they appear to have been generated using a large language model without rigorous scrutiny.
Report generation functionality is almost always present in database systems, [citation needed] where the source of the data is the database itself. It can also be argued that report generation is part of the purpose of a spreadsheet. Standalone report generators may work with multiple data sources and export reports to different document formats.
The generator is decomposed into a pyramid of generators =, with the lowest one generating the image () at the lowest resolution, then the generated image is scaled up to (()), and fed to the next level to generate an image (+ (())) at a higher resolution, and so on. The discriminator is decomposed into a pyramid as well.
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On the other hand, a problem is AI-Hard if and only if there is an AI-Complete problem that is polynomial time Turing-reducible to . This also gives as a consequence the existence of AI-Easy problems, that are solvable in polynomial time by a deterministic Turing machine with an oracle for some problem.
Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words.