Click the above“Machine Learning and Generative Adversarial Networks” to follow and star Get interesting and fun cutting-edge content! Author on Zhihu: Mr. Good Good, please delete if infringing https://zhuanlan.zhihu.com/p/361893386 1 Background Knowledge The Attention mechanism was first proposed in the field of visual images, probably in the 1990s, but it really gained popularity with the … Read more
Produced by Machine Learning Algorithms and Natural Language Processing @Official Account Original Column Author Don.hub Position | Algorithm Engineer at JD.com School | Imperial College London Outline Intuition Analysis Pros Cons From Seq2Seq To Attention Model Seq2Seq is important, but its flaws are obvious Attention was born Write the encoder and decoder model Taxonomy of … Read more
Source | Zhihu Author | JayLou Link | https://zhuanlan.zhihu.com/p/53682800 Editor | Deep Learning Matters WeChat Public Account This article is for academic sharing only. If there is any infringement, please contact us to delete. This article summarizes the attention mechanism (Attention) in natural language processing in a Q&A format and provides an in-depth analysis of … Read more
The attention mechanism is mentioned in both of the following articles: How to make chatbot conversations more informative and how to automatically generate text summaries. Today, let’s take a look at what attention is. This paper is considered the first work using the attention mechanism in NLP. They applied the attention mechanism to Neural Machine … Read more
The attention mechanism can be likened to how humans read a book. When you read, you don’t treat all content equally; you may pay more attention to certain keywords or sentences because they are more important for understanding the overall meaning. Image: Highlighting key content in a book with background colors and comments. The role … Read more
Abstract： In humans, attention is a core attribute of all perceptual and cognitive operations. Given our limited capacity to process competitive sources of information, the attention mechanism selects, adjusts, and focuses on information most relevant to behavior. For decades, the concept and function of attention have been studied across philosophy, psychology, neuroscience, and computer science. … Read more
Click the “AI Meets Machine Learning” above to select the “star” public account Original content delivered first-hand 1. What is Attention Mechanism? In the past two years, attention models (Attention Models) have been widely used in various types of deep learning tasks such as natural language processing, image recognition, and speech recognition, making it one … Read more
[Introduction]The Attention mechanism originates from mimicking human thinking patterns and has been widely applied in machine translation, sentiment classification, automatic summarization, automatic question answering, dependency analysis, and other machine learning applications. The editor has compiled a review on the application of Attention mechanisms in NLP titled An Introductory Survey on Attention Mechanisms in NLP Problems, … 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 teachers, and industry researchers. The Vision of the Community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning, especially for beginners. Reprinted … Read more
Phidata: A framework for building AI assistants using LLM function calls, allowing LLMs to intelligently choose actions based on responses by executing functions. The assistant has built-in memory, knowledge, storage, and tools, making it easy to build various applications such as knowledge assistants, data assistants, Python assistants, customer assistants, research assistants, marketing assistants, travel assistants, … Read more