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Prompt injection is a family of related computer security exploits carried out by getting a machine learning model (such as an LLM) which was trained to follow human-given instructions to follow instructions provided by a malicious user. This stands in contrast to the intended operation of instruction-following systems, wherein the ML model is ...
Prompt injection is a family of related computer security exploits carried out by getting a machine learning model which was trained to follow human-given instructions (such as an LLM) to follow instructions provided by a malicious user. This stands in contrast to the intended operation of instruction-following systems, wherein the ML model is ...
Some examples of commonly used question answering datasets include TruthfulQA, Web Questions, TriviaQA, and SQuAD. [123] Evaluation datasets may also take the form of text completion, having the model select the most likely word or sentence to complete a prompt, for example: "Alice was friends with Bob. Alice went to visit her friend, ____". [1]
Wiki markup quick reference (PDF download) For a full list of editing commands, see Help:Wikitext; For including parser functions, variables and behavior switches, see Help:Magic words; For a guide to displaying mathematical equations and formulas, see Help:Displaying a formula; For a guide to editing, see Wikipedia:Contributing to Wikipedia
Experienced editors may ask an LLM to improve the grammar, flow, or tone of pre-existing article text. Rather than taking the output and pasting it directly into Wikipedia, you must compare the LLM's suggestions with the original text, and thoroughly review each change for correctness, accuracy, and neutrality. Summarizing a reliable source.
Another key design goal was readability, that the language be readable as-is, without looking like it has been marked up with tags or formatting instructions, [9] unlike text formatted with "heavier" markup languages, such as Rich Text Format (RTF), HTML, or even wikitext (each of which have obvious in-line tags and formatting instructions ...
Ernie Bot is based on particular Ernie foundation models, including Ernie 3.0, Ernie 3.5, and Ernie 4.0. The training process starts from pre-training, learning from trillions of data points and billions of knowledge pieces. This was followed by refinement through supervised fine-tuning, reinforcement learning with human feedback, and prompt. [19]
This page in a nutshell: Avoid using large language models (LLMs) to write original content or generate references. LLMs can be used for certain tasks (like copyediting, summarization, and paraphrasing) if the editor has substantial prior experience in the intended task and rigorously scrutinizes the results before publishing them.