Click above toComputer Vision Alliance get more insights For academic sharing only, does not represent the position of this public account. Contact for deletion in case of infringement. Reprinted from: Machine Heart Recommended notes from 985 AI PhD Zhou Zhihua’s “Machine Learning” handwritten notes are officially open-source! Includes PDF download link, 2500 stars on GitHub! … Read more
“The stone from other hills can serve to polish jade.” Only by standing on the shoulders of giants can we see further and go farther. On the path of scientific research, we need to leverage favorable conditions to move forward faster. Therefore, we have specially collected and organized some practical code links, datasets, software, programming … Read more
Click the card below to follow Computer Vision Daily. AI/CV heavy content delivered promptly. Click to enter—>【CV Technology】 WeChat group Scan to join the CVer Academic Circle, to gain access to the latest top conference/journal paper ideas and materials from beginner to advanced in CV, as well as cutting-edge projects and applications! Highly recommended for … Read more
Click on the above “AI Meets Machine Learning“, and select “Star” public account Original content delivered first-hand In the previous article, we discussed the concept of attention. This article builds on that, providing a deeper understanding of the ideas surrounding attention and the latest self-attention mechanism. 1. The Essence of Attention Mechanism To better understand … Read more
Machine Heart reports Machine Heart Editorial Team “Big model developers, you are wrong.” “I discovered a bug in the attention formula that no one has found for eight years. All Transformer models, including GPT and LLaMA, are affected.” Yesterday, a statistician named Evan Miller stirred up a storm in the AI field with his statement. … Read more
Click the “MLNLP” above and select the “Star” public account Important content, delivered as soon as possible Editor: Yi Zhen https://www.zhihu.com/question/349474623 This article is for academic sharing only; if there is any infringement, it will be deleted. Reports on machine learning algorithms and natural language processing How to Incorporate Attention Mechanism in NLP? Author: Yi … Read more
Introduction The left side of the figure below shows the traditional Seq2Seq model (which encodes a sequence and then decodes it back into a sequence). This is a conventional LSTM-based model, where the hidden state at a given timestamp in the Decoder only depends on the current timestamp’s hidden state and the output from the … Read more
Continuing from the last time: Attention Mechanism Series 1 – Why Introduce Attention Mechanism First, let’s talk about the role of the attention mechanism: It allows the model to dynamically focus on and process any part of the entire input sequence, without being limited by a fixed window size. This way, the model can selectively … Read more
Attention Mechanisms have become the foundational architecture for model design; it’s almost a given that a good model should incorporate some form of attention. This article summarizes the current state of Attention Mechanisms by introducing 17 mainstream types of attention mechanisms, explaining their basic principles and computational methods, and providing their sources along with corresponding … Read more
Click the “MLNLP” above to select the “Star” public account Heavy-duty content delivered promptly Author: Gu Yuxuan, Harbin Institute of Technology SCIR References NAACL 2019 “Attention is Not Explanation” ACL 2019 “Is Attention Interpretable?” EMNLP 2019 “Attention is Not Not Explanation” This article will explore the interpretability of the attention mechanism. Introduction Since Bahdanau introduced … Read more