Pre-trained language modelBERTGPTWith the rapid progress in Natural Language Processing (NLP), Pre-trained Language Models (PLM) such as BERT, BioBERT, and ChatGPT have shown great potential in various medical NLP tasks. This paper surveys the cutting-edge achievements in applying PLMs to ...
论文:Pre-trained Models for Natural Language Processing: A Survey 首先简要介绍了语言表示学习及相关研究进展; 其次从四个方面对现有 PTM (Pre-trained Model) 进行系统分类(Contextual、Architectures、Task Types、Extensions); 再次描述了如何将 PTM 的知识应用于下游任务; 最后展望了未来 PTM 的一些潜在发展方向。
Pre-trained language models (PLMs) are first trained on a large dataset and then directly transferred to downstream tasks, or further fine-tuned on another small dataset for specific NLP tasks. Early PLMs, such as Skip-Gram [1] and GloVe [2], are shallow neural networks, and their word e...
论文名:Pre-trained Language Models for Text Generation A Survey 作者:Junyi Li, Tianyi Tang, Wayne Xin Zhao, Jian-Yun Nie, Ji-Rong WenAuthors Info & Claims 发布时间:2024-04-25 引用次数: 338 …
Pre-Trained Language Models (PLMs) refer to neural networks that are trained on large-scale unlabeled corpora and can be further fine-tuned for various downstream tasks. These models, such as those used in NLP, contain a significant amount of linguistic knowledge in their parameters, making them...
This chapter presents the main architecture types of attention-based language models, which describe the distribution of tokens in texts: Autoencoders similar to BERT receive an input text and produce a contextual embedding for each token. Autoregressive
论文阅读:Pre-trained Models for Natural Language Processing: A Survey 综述:自然语言处理的预训练模型,程序员大本营,技术文章内容聚合第一站。
跨模态预训练任务包括Masked Language Modeling (MLM)、Masked Region Prediction (MRP)和Image-Text Matching (ITM)。MLM和MRP有助于学习图像和文本之间的细粒度相关性，而ITM在粗粒度级别上使二者进行对齐，即要求模型确定图像和文本是否匹配并输出对齐概率。跨模态对比学习（CMCL）输入图像和文本匹配的正...
Paper tables with annotated results for How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey
trained models, new paradigms have emerged to solve the classic challenges. Such methods have become mainstream in current research with increasing attention and rapid advances. In this paper, we present a comprehensive overview of how vision-language tasks benefit from pre-trained models. First, we...