Source: Deep Learning and Large Models (LLM) This article is approximately 3500 words long and is recommended for a 9-minute read. This article delves into the development of Retrieval-Augmented Generation (RAG), from basic concepts to the latest technologies. 4. Overview of Existing RAG Frameworks Agent-Based RAG A new agent-based Retrieval-Augmented Generation (RAG) framework adopts a … Read more
A Survey of Query Optimization in Large Language Models Paper Link:https://arxiv.org/pdf/2412.17558 Published by: Tencent Large Language Models (LLMs) are becoming increasingly popular, but they also face challenges such as “hallucination” when dealing with domain-specific tasks or those requiring specialized knowledge. Retrieval-Augmented Generation (RAG) technology has emerged as a key method for enhancing model performance, with … Read more
Since OpenAI officially released ChatGPT in November 2022, the AI technology ecosystem has experienced rapid advancement. The public has transitioned from a state of confusion to a thrilling and exciting experience, and now to feelings of unease due to the cost-cutting and efficiency improvements brought by their respective companies. The world is changing so quickly, … Read more
Recently, the world-renowned management consulting firm Boston Consulting Group (BCG) released a highly insightful report predicting that AI Agents will spark a revolution across various industries, prompting profound reflections on future work models, business models, and even the shape of human society. As Yuval Noah Harari, author of “Sapiens: A Brief History of Humankind,” stated: … Read more
Editor’s Overview This reading list published by Latent Space selects 50 papers in the field of AI engineering, covering ten core modules, providing valuable resources for AI engineers and other professionals to enhance their skills. The cutting-edge large language model (LLM) section covers the latest developments of major series models; the benchmarking and evaluation module … Read more
Hi, I’m GuiGui, exploring AI. If you like the content here, please follow to stay updated! Slash Little Ghost Have you ever encountered a situation where you eagerly ask AI a question, only for it to provide a completely absurd answer? For instance, if you ask, “What is Python?” and it responds, “Python is a … Read more
In recent years, artificial intelligence has made significant leaps, primarily due to large language models (LLMs). LLMs are very good at understanding and generating human-like text, leading to the creation of various new tools, such as advanced chatbots and AI writers. Although LLMs excel at generating fluent, human-like text, they sometimes struggle with factual accuracy. … 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 enterprise 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. Reposted … Read more
Detailed Explanation of RAG 2.0 Architecture The so-called RAG, short for Retrieval-Augmented Generation, combines retrieval and generation technologies to enhance the effectiveness of text generation tasks. Its working principle combines the advantages of retrieval models and generation models to address some challenges and issues in text generation. RAG 2.0, on the other hand, is an … Read more
Introduction Many product managers and engineers familiar with RAG often complain, “It only takes a week to produce a demo with RAG, but it takes at least six months to reach a production-level standard!” This is a realistic issue for the current industrial implementation of RAG. The RAG framework is very simple and understandable, and … Read more