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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.
Part 1 of the manual approaches the process of research and writing. This includes providing "practical advice" to formulate "the right questions, read critically, and build arguments" as well as helping authors draft and revise a paper. [3] Initially added with the seventh edition of the manual, this part is adapted from The Craft of Research ...
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 ]
Question answering systems in the context of [vague] machine reading applications have also been constructed in the medical domain, for instance related to [vague] Alzheimer's disease. [3] Open-domain question answering deals with questions about nearly anything and can only rely on general ontologies and world knowledge. Systems designed for ...
A classic example of a problem which a regular grammar cannot handle is the question of whether a given string contains correctly nested parentheses. (This is typically handled by a Chomsky Type 2 grammar, also termed a context-free grammar .)
The answer to a research question will help address a research problem or question. [5] Specifying a research question, "the central issue to be resolved by a formal dissertation, thesis, or research project," [6] is typically one of the first steps an investigator takes when undertaking research.
Text Python Any 2013 1.0.1 (2021) Unlicense (PD) perldoc: Larry Wall: Text Perl Any 1994 5.16.3 Artistic, GPL phpDocumentor: Joshua Eichorn Text PHP Any 2000 3.0.0 LGPL for 1.x, MIT for 2+ pydoc: Ka-Ping Yee [1] Text Python Any 2000 in Python core Python: RDoc: Dave Thomas Text C, C++, Ruby Any 2001/12/14 in Ruby core Ruby: ROBODoc: Frans ...
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.
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