Analyst Network of Machine Heart Author: Wang Zijia Editor: H4O This article starts from the ancestor level word2vec and systematically sorts out the “genealogy” of GPT and the large NLP “family group” led by word2vec. GPT did not emerge out of nowhere; it is the result of the efforts of many people and a long … Read more
The official Chinese version of the PyTorch tutorial is here. PyTorch is one of the most popular deep learning frameworks recently, but its official Chinese tutorial has been long awaited. Recently, a complete official Chinese version of the PyTorch tutorial has been released, allowing readers to better learn and understand the relevant details of PyTorch. … Read more
This article summarizes the attention mechanism in natural language processing (NLP) in a Q&A format and provides an in-depth analysis of the Transformer. Table of Contents 1. Analysis of Attention Mechanism1. Why introduce the attention mechanism?2. What types of attention mechanisms are there? (How are they classified?)3. What is the computational process of the attention … Read more
If you like it, please follow CV Circle ! The attention mechanism has become very popular in recent years. So, what are the origins and current developments of the attention mechanism? Let’s follow the author, Mr. Haohao, and take a look. Author of this article: Mr. Haohao, authorized for reprint Link: https://zhuanlan.zhihu.com/p/361893386 1 Background Knowledge … Read more
Recently, I plan to organize the application of Attention in deep recommendation systems, so I wrote this introductory article about Attention. Since it was proposed in the 2015 ICLR paper “Neural machine translation by jointly learning to align and translate”, Attention has flourished in the fields of NLP and computer vision. What is so special … Read more
Click belowCard, follow “AICV and Frontier“ Paper: https://arxiv.org/abs/2412.09262 Code: https://github.com/DAMO-NLP-SG/VideoLLaMA3 01 Introduction A more advanced multimodal foundation model for image and video understanding. The core design philosophy of VideoLLaMA3 is vision-centric: Vision-centric training paradigm Vision-centric framework design. The key point of the vision-centric training paradigm is that high-quality image-text data is crucial for understanding both … Read more
Is there a difference between LLM large models and embedding large models in the knowledge base domain? Why is it necessary to set up a separate embedding large model in the RAG field? In the field of artificial intelligence, large language models (LLMs) and embedding models are two key technologies in natural language processing (NLP), … Read more
Introduction Hello everyone, I am Liu Cong from NLP. RAG (Retrieval-Augmented Generation) finds information fragments relevant to user questions through a retrieval system, utilizing large models to synthesize an answer. This greatly addresses issues such as hallucination and outdated information in large models, and has become an important means for the practical application of large … Read more
Click on “Deephub Imba“, follow the public account, and don’t miss out on great articles! There have been many articles about Retrieval-Augmented Generation (RAG). If we could create a trainable retriever, or if the entire RAG could be customized like fine-tuning a large language model (LLM), we would definitely achieve better results. However, the current … Read more
Happy New Year, everyone! Today, I will interpret Baichuan’s RAG approach. Baichuan Intelligent has a profound background in search; let’s see how they navigated the pitfalls of RAG! In general, Baichuan combines a long context model (192k) with search enhancement methods to address knowledge updates and reduce model hallucinations, achieving 95% accuracy on a dataset … Read more