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
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
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 Attention as soft alignment in neural machine translation in 2014, a large amount of … Read more
Follow the WeChat official account “ML_NLP“ Set as “Starred“, delivering heavy content to you first! Source | Zhihu Link | https://zhuanlan.zhihu.com/p/78850152 Author | Ailuo Yue Editor | Machine Learning Algorithms and Natural Language Processing WeChat Official Account This article is for academic sharing only. If there is any infringement, please contact us for removal. 1 … Read more
Follow our WeChat public account “ML_NLP“ Set as “Starred“, delivering heavy content to you first! Source | Zhihu Address | https://zhuanlan.zhihu.com/p/339123850 Author | Ma Dong Shen Me Editor | Machine Learning Algorithms and Natural Language Processing WeChat Public Account This article is for academic sharing only. If there is any infringement, please contact us to … Read more
1. Understanding the Principle of Attention Mechanism The Attention mechanism, in simple terms, refers to the output y at a certain moment and its attention on various parts of the input x. Here, attention represents weights, indicating the contribution of each part of the input x to the output y at that moment. Based on … Read more
Click the “AI Park” above to follow the public account and choose to add “Star Mark” or “Top”. Author: Raimi Karim Translator: ronghuaiyang Introduction Previously, I shared several articles on attention, feeling unsatisfied. This time, I will explain the Attention mechanism using GIFs, making it easy to understand, and explain how it is used in … Read more
The Attention mechanism is a technique in deep learning, particularly widely used in Natural Language Processing (NLP) and computer vision. Its core idea is to mimic the human attention mechanism, where humans focus on certain key parts of information while ignoring less important information. In machine learning models, this can help the model better capture … Read more
This article focuses on explaining MLA (Multi-Head Latent Attention). Note: During my learning process, I usually encounter some knowledge blind spots or inaccuracies, and I recursively learn some extended contexts. This article also interprets the background of MLH’s proposal, the problems it aims to solve, and the final effects step by step along with some … Read more