Approximately 3500 words, recommended reading time 10 minutes. Today, we will explore the core technologies behind large models! 1. Transformer The Transformer model is undoubtedly the solid foundation of large language models, ushering in a new era in deep learning. In the early stages, Recurrent Neural Networks (RNNs) were the core means of handling sequential … Read more
Follow the WeChat public account “ML_NLP” Set as “Starred” to receive heavy content promptly! Reprinted from | PaperWeekly ©PaperWeekly Original · Author｜Hai Chenwei School｜Master’s student at Tongji University Research Direction｜Natural Language Processing In the current NLP field, Transformer/BERT has become a fundamental application, and Self-Attention is the core part of both. Below, we attempt to … Read more
来源：DeepHub IMBA This article is approximately 1800 words long and is recommended to be read in 5 minutes. This article will provide a detailed introduction to the principles and mechanisms of the masks in attention mechanisms. The attention mechanism mask allows us to send batches of data of varying lengths into the transformer at once. … Read more
In the past two years, the BERT model has become very popular. Most people know about BERT but do not understand what it specifically is. In short, the emergence of BERT has completely changed the relationship between pre-training to generate word vectors and downstream specific NLP tasks, proposing the concept of training word vectors at … Read more
Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered first time! From | Zhihu Address | https://zhuanlan.zhihu.com/p/91839581 Author | Zhao Qiang Editor | Machine Learning Algorithms and Natural Language Processing Public Account This article is for academic sharing only. If there is any infringement, please contact the backend for deletion. Attention is being … Read more
Follow the public account “ML_NLP” Set as “starred” to receive heavy content promptly! Author丨Electric Light Phantom Alchemy @ Zhihu Source丨https://zhuanlan.zhihu.com/p/362366192 Editor丨Machine Learning Algorithms and Natural Language Processing Attention has become a hot topic in the entire AI field, whether in machine vision or natural language processing, it is inseparable from Attention, transformer, or BERT. Below, … Read more
Source: DeepHub IMBA This article is approximately 4600 words long and is recommended to be read in 10 minutes. In this article, we will combine text and knowledge graphs to enhance the performance of our RAG. In our previous articles, we introduced examples of combining knowledge graphs with RAG. In this article, we will combine … Read more
Follow the public account "ML_NLP" Set as “Starred“, heavy content will be delivered to you first! Author: Jiang Runyu, Harbin Institute of Technology SCIR Introduction In recent years, one of the most impressive achievements in the field of NLP is undoubtedly the pre-trained models represented by BERT proposed by Google. They continuously refresh records (both … Read more
MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP master’s and doctoral students, university professors, and corporate researchers. The community’s vision is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, especially for beginners. Reprinted from | … Read more
Follow the public account “ML_NLP“ Set as “Starred“, delivering heavy content promptly! Original · Author | TheHonestBob School | Hebei University of Science and Technology Research Direction | Natural Language Processing 1. Introduction There are countless good articles online about this topic, all of which are very detailed. The reason I am writing this blog … Read more