KM scaling law. In 2020, Kaplan et al. [30] (the OpenAI team) firstly proposed to model the power-law relationship of model performance with respective to three major factors, namelymodel size (N), dataset size (D), and the amount of training compute (C), for neural language models. ...
Each pie chart shows the relative magnitude of the averaged score from the two models. The size of each chart is proportional to the overall cumulative score across the six criteria Full size image Discussion In this study, we aimed to investigate the potential utility of large language models ...
Fig. 1: Large language models (LLMs) in medicine. Full size image Data availability No datasets were created in the context of this work. Examples of LLM outputs are provided in theSupplementary Data. References Download references Acknowledgements ...
这些类人模型主要依靠两个组件(大型语言模型(large language models, llm)和视觉词汇网络),不仅可以根据用户输入的图像进行对话,而且在简单的下游任务上也表现良好,如VQA、图像标题、OCR等。因此,不可否认的是,大型视觉语言模型(LVLMs)正在推动人工智能社区朝着人工通用智能(AGI)的方向发展。 流行的类似GPT-4[32]的...
Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation;Patrick Fernandes et al Reasoning with Language Model Prompting: A Survey;Shuofei Qiao et al Towards Reasoning in Large Language Models: A Survey;Jie Huang et al ...
Large language models (LLMs) [3,4,5,6], trained on diverse datasets, have demonstrated an impressive ability to generate human-like text, answer questions, and even provide insights on complex problems. These models mainly build on the Transformer architecture [7,8,9] and advanced training ...
🔥🔥🔥Woodpecker: Hallucination Correction for Multimodal Large Language Models Paper|Source Code This is the first work to correct hallucination in multimodal large language models. ✨ 📑 If you find our projects helpful to your research, please consider citing: ...
“It might be a medium-size problem right now, but it will become a really big problem in the future as models become more powerful.” Barak works on OpenAI’s superalignment team, which was set up by the firm’s chief scientist, Ilya Sutskever, to figure out how to stop a ...
LLMs(large language models):可以生成人类语言的深度学习模型,因此被称为语言模型(language models)。该模型有数十亿个参数,并在数十亿个单词的基础上进行训练,因此被称为大语言模型。 MLOps (machine learning operations):用于管理基于ML应用的生命周期一系列工具和最佳实践。
左图是六大类任务,右图则以动词+宾语的形式给出具体描述,比如create+table, create+chart 【atomic action】元动作,是对于电子表格操作功能的一系列api,比如值修改,格式设置,公式和函数等。具体由以下部分组成:{API名称,类型化参数列表,用法文档字符串,几个用法示例}。这些atomic action可以在不同的电子表格平台上...