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Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.
Cite4Wiki, an XUL-based add-on for Pale Moon to generate {} and {} for the browser's current page. citemark – A bookmarklet to help create {} templates; see the developer's page for details; RefScript: A bookmarklet that generates references with a single click. Works with a few news websites (BBC, Daily Mirror, Daily Telegraph, Huffington ...
As we programmed, we examined the process and tried to think of ways to abstract these steps to incorporate them into higher-level language. This led to the development of interpreters, assemblers, compilers, and generators—programs designed to operate on or produce other programs, that is, automatic programming ."
Sometimes articles are created by a bot.The issue has been controversial, this page discusses some arguments for and against it and the current guidance. The current guideline for creating articles with a bot is set out at WP:MASSCREATION meaning consensus is required to ensure that they comply with Wikipedia's guidelines.
As before, the list of footnotes is automatically generated in a "Notes" or "Footnotes" section, which immediately precedes the "References" section containing the full citations to the source. Short citations can be written manually, or by using either the {{sfn}} or {{harvnb}} templates or the {{r}} referencing template. (Note that templates ...
CoT examples can be generated by LLM themselves. In "auto-CoT", [41] a library of questions are converted to vectors by a model such as BERT. The question vectors are clustered. Questions nearest to the centroids of each cluster are selected. An LLM does zero-shot CoT on each question. The resulting CoT examples are added to the dataset.
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