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Free writing is traditionally regarded as a prewriting technique practiced in academic environments, in which a person writes continuously for a set period of time with limited concern for rhetoric, conventions, and mechanics, sometimes working from a specific prompt provided by a teacher. [1]
The Postmodernism Generator is a computer program that automatically produces "close imitations" of postmodernist writing. It was written in 1996 by Andrew C. Bulhak of Monash University using the Dada Engine, a system for generating random text from recursive grammars. [1] A free version is also hosted online.
A paper generator is computer software that composes scholarly papers in the style of those that appear in academic journals or conference proceedings. Typically, the generator uses technical jargon from the field to compose sentences that are grammatically correct and seem erudite but are actually nonsensical. [ 1 ]
Similarly, an image model prompted with the text "a photo of a CEO" might disproportionately generate images of white male CEOs, [128] if trained on a racially biased data set. A number of methods for mitigating bias have been attempted, such as altering input prompts [129] and reweighting training data. [130]
An admissions or application essay, sometimes also called a personal statement or a statement of purpose, is an essay or other written statement written by an applicant, often a prospective student applying to some college, university, or graduate school. The application essay is a common part of the university and college admissions process.
Writing a Wikipedia article: Summarize the most important things your sources say. Don't copy/paste wording from your sources; instead, summarize the ideas in the source using your own words. Summarization is more than just changing a few words around here and there. Only add information supported by your sources.
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These models take text prompts as input and use them to generate AI-generated images. Text-to-image models typically do not understand grammar and sentence structure in the same way as large language models, [48] thus may require a different set of prompting techniques. Text-to-image models do not natively understand negation.
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