Discussion on Absolute, Relative, and Rotational Position Encoding in Transformers

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Discussion on Absolute, Relative, and Rotational Position Encoding in Transformers

Click the card below to follow the “AI Frontier Express” public account Various important resources delivered promptly Reprinted from Zhihu: Yao Yuan Link: https://zhuanlan.zhihu.com/p/17311602488 1. Introduction The attention mechanism in Transformer [1] can effectively model the correlations between tokens, achieving significant performance improvements in many tasks. However, the attention mechanism itself does not have the … Read more

Unveiling the Mathematical Principles of Transformers

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Unveiling the Mathematical Principles of Transformers

Machine Heart Reports Editor: Zhao Yang Recently, a paper was published on arXiv, providing a new interpretation of the mathematical principles behind Transformers. The content is extensive and rich in knowledge, and I highly recommend reading the original. In 2017, Vaswani et al. published “Attention Is All You Need,” marking a significant milestone in the … Read more

Where Does the Context Learning Ability of Transformers Come From?

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Where Does the Context Learning Ability of Transformers Come From?

Machine Heart reports Machine Heart Editorial Department With a theoretical foundation, we can perform deep optimization. Why is the performance of transformers so good? Where does the context learning (In-Context Learning) ability it brings to many large language models come from? In the field of artificial intelligence, transformers have become the dominant model in deep … Read more

Transformers as Support Vector Machines

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Transformers as Support Vector Machines

Machine Heart reports Editors: Danjiang, Xiaozhou SVM is all you need; Support Vector Machines are never out of date. The Transformer is a new theoretical model of Support Vector Machines (SVM) that has sparked discussion in academia. Last weekend, a paper from the University of Pennsylvania and the University of California, Riverside, sought to explore … Read more

A Comprehensive Guide to Building Transformers

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A Comprehensive Guide to Building Transformers

This article aims to introduce the Transformer model. Originally developed for machine translation, this model has since been widely applied in various fields such as computer recognition and multimodal tasks. The Transformer model introduces self-attention mechanisms and positional encoding, and its architecture mainly consists of an input part, an output part, and encoders and decoders. … Read more

Understanding the Transformer Model: A Visual Guide

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Understanding the Transformer Model: A Visual Guide

Introduction In recent years, deep learning has made tremendous progress in the field of Natural Language Processing (NLP), and the Transformer model is undoubtedly one of the best. Since the Google research team proposed the Transformer model in their paper “Attention is All You Need” in 2017, it has become the cornerstone for many NLP … Read more

Practical Guide to Object Detection Using Vision Transformer

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Practical Guide to Object Detection Using Vision Transformer

Click the card below to follow the WeChat public account “Python for Beginners” Object detection is a core task in computer vision that drives the development of technologies ranging from autonomous vehicles to real-time video surveillance. It involves detecting and locating objects within an image, and recent advances in deep learning have made this task … Read more

Overview of Transformer Compression

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Overview of Transformer Compression

Large models based on the Transformer architecture are playing an increasingly important role in artificial intelligence, especially in the fields of natural language processing (NLP) and computer vision (CV). Model compression methods reduce their memory and computational costs, which is a necessary step for implementing Transformer models on practical devices. Given the unique architecture of … Read more

WTPose Framework: Enhancing Pose Estimation with Waterfall Module Based on Transformer

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WTPose Framework: Enhancing Pose Estimation with Waterfall Module Based on Transformer

Click the card below to follow the 「Intelligent Book Boy」 public account Click to join👉「Intelligent Book Boy」 group chat Want to learn more: Cutting-edge AI visual perception full-stack knowledge👉「Classification, Detection, Segmentation, Key Points, Lane Line Detection, 3D Vision (Segmentation, Detection), Multi-modal, Object Tracking, NerF」 Industry Technical Solutions👉「AI Security, AI Healthcare, AI Autonomous Driving」 AI Model … Read more

Real-Time Detection Transformer (RT-DETR) Combined with EBC for Superior Image Representation

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Real-Time Detection Transformer (RT-DETR) Combined with EBC for Superior Image Representation

Click the card below to follow「AI Vision Engine」public account ( Note when adding: direction + school/company + nickname/name ) Event-based cameras (EBCs) are a biologically inspired alternative to traditional cameras, emerging due to their advantages in energy efficiency, temporal resolution, and high dynamic range. However, developing corresponding image analysis methods is quite challenging due to … Read more