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Self-refine [38] prompts the LLM to solve the problem, then prompts the LLM to critique its solution, then prompts the LLM to solve the problem again in view of the problem, solution, and critique. This process is repeated until stopped, either by running out of tokens, time, or by the LLM outputting a "stop" token.
Identifying AI-assisted edits is difficult in most cases since the generated text is often indistinguishable from human text. Some exceptions are if the text contains phrases like "as an AI model" or "as of my last knowledge update" and if the editor copy-pasted the prompt used to generate the
A large language model (LLM) is a type of computational model designed for natural language processing tasks such as language generation.As language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a self-supervised and semi-supervised training process.
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.
Apart from the a possibility that saving an LLM output may cause verbatim non-free content to be carried over to the article, these models can produce derivative works. For example, an LLM can rephrase a copyrighted text using fewer, the same, or more words than the original – editors should mind the distinction between a summary and an ...
BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [3]
Llama (Large Language Model Meta AI, formerly stylized as LLaMA) is a family of autoregressive large language models (LLMs) released by Meta AI starting in February 2023. [2] [3] The latest version is Llama 3.3, released in December 2024.
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.