维基百科(Wikipedia)是美国维基媒体基金会的互联网百科项目,其内容可能受到立场、信息来源等因素影响,请客观看待。正文内容不代表译者观点。辽观提供的翻译仅供参考。文中可能包含无法从中国内地访问的链接。辽观所搬运的词条文本与维基百科一道同样遵循CC BY-SA 4.0协议(辽观搬运的中英文对照版本),在符合协议要求的...
Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Modelsarxiv.org/abs/2402.14207 本工作构建了一个基于大型语言模型(LLM)的写作系统STORM,旨在自动化地从零开始撰写类似维基百科的长篇、结构化的文章。STORM通过模拟多角度提问和检索互联网上可信的来源来创建文章大纲,并据此生成全文。
What exactly does “large” entail as it applies to language models? According to Wikipedia, “a language model…can generate probabilities of a series of words, based on text corpora in one or multiple languages it was trained on.” LLMs are the most advanced kind of language model, “com...
We study how to apply large language models to write grounded and organized long-form articles from scratch, with comparable breadth and depth to Wikipedia pages. This underexplored problem poses new challenges at the pre-writing stage, including how to research the topic and prepare an outline ...
An illustration of a typical data preprocessing pipeline for pre-training large language models. 预训练数据对LLMs的影响 与小规模PLMs不同,由于对计算资源的巨大需求,通常不可能多次迭代LLMs的预训练。因此,在训练LLMs之前构建一个准备充分的预训练语料库尤为重要。在本部分中,我们讨论预训练语料库的质量和分布...
In essence, LMs are predictors for the subsequent token in a sequence. To achieve this, most LMs undergo an extremely resource-intensive training process, in which they learn to predict the next token by packaging extensive text collections such as books, Wikipedia articles, or even the entire ...
Large language models (LLM). 更大规模的PLM,GPT3,PaLM,产生emergent abilities Researchers find that scaling PLM (e.g., scaling model size or data size) often leads to an improved model capacity on downstream tasks (i.e., following the scaling law [30]). ...
including webpages from CommonCrawl, GitHub, Wikipedia and Project Gutenberg. Llama was effectively leaked and spawned many descendants, including Vicuna and Orca. Llama is available under an open license, allowing for free use of the models. Lllama models are available in many locations includingll...
Link A VQA dataset that focuses on asking information-seeking questions OVEN Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities Link A dataset that focuses on recognizing the Visual Entity on the Wikipedia, from images in the wildAbout...
RAG bridges these gaps by incorporating external knowledge bases. When a prompt is received, RAG queries a vector database containing embeddings of external documents (e.g., Wikipedia entries, proprietary databases or recent news articles). This real-time retrieval of up-to-date information allows...