AI Knowledge Base

1. Background and Issues With the rapid development of Artificial Intelligence (AI) technology, especially the advancement of diffusion modeling, AI has been able to generate very realistic portrait images. For example, technologies like InstantID require only one photo to generate multiple new images with the same identity...

NoLiMA, released in February 2025, is a Large Language Model (LLM) method for assessing long text comprehension. Unlike traditional Needle-in-a-Haystack (NIAH) tests that rely on keyword matching, it is most...

Have you ever been in a situation where you type a keyword into a search engine and what comes up is not what you want? Or, you want to search for something, but you don't know what words to use to express the most accurate? Don't worry, "query expansion" technology can help you solve these problems. Recently, the query expansion...

The field of generative AI is currently evolving rapidly, with new frameworks and technologies emerging. Therefore, readers need to be aware that the content presented in this paper may be time-sensitive. In this paper, we will take an in-depth look at two of the leading frameworks for building LLM applications: LangChain and LangGr...

Understanding the three key concepts of MCP Server, Function Call, and Agent is essential in the burgeoning field of Artificial Intelligence (AI), especially Large Language Modeling (LLM). They are the cornerstones of AI systems...

Introduction Have you ever wondered how the chatbots we use today, such as OpenAI's models, determine whether a question is safe and should be answered? In fact, these Large Reasoning Models (...

Recently found an open source project, it provides a good RAG ideas, it will DeepSeek-R1 reasoning ability combined with Agentic Workflow applied to RAG retrieval Project address https://github...

In recent years, the field of Artificial Intelligence (AI) has made significant progress in its reasoning capabilities. After OpenAI demonstrated the powerful inference potential of large language models (LLMs) last year, Google DeepMind, Alibaba, DeepSeek, and Anthropi...

多智能体系统 (Multi-Agent System, MAS) 是一个由多个交互的智能体 (Intelligent Agent) 组成的计算系统。多智能体系统可用于解决单个智能体或单体系统难以解决或...

In recent years, with the rapid development of large-scale language modeling (LLM), the capability of Multi-Agent Systems (MAS) has been significantly improved. These systems are not only able to automate tasks, but also exhibit near-human reasoning capabilities. However, the transmission ...

Large-scale language modeling (LLM) is playing an increasingly important role in the field of artificial intelligence. In order to better understand and apply LLMs, we need to gain a deeper understanding of their core concepts. In this paper, we will focus on three key concepts, namely Token, Maximum Output Length, and Context Length, to help readers clear...

Recently, the terms Autonomous AI (Agentic AI), AI Agents, and Agents have appeared frequently in the public eye. Frankly, despite being data analysts and scientists, people in the industry used to have no idea what this...

In recent years, Artificial Intelligence (AI) technologies have sparked a profound change in the programming field. From v0 and bolt.new to programming tools that integrate Agent technology, such as Cursor and Windsurf, AI Coding has demonstrated a significant role in the development of software...

In the age of AI-assisted programming, we want AI to generate code that is not just static text, but can be parsed, edited, previewed, and even executed. This demand has given rise to a new interaction paradigm, Artifact. In this article, we'll go from theoretical concepts to practical realities...

In this paper, we present a summary report of Kapa.ai's recent exploration of inference models such as OpenAI's o3-mini in the Retrieval-Augmented Generation (RAG) system...

DeepSeek R1 has demonstrated strong inference capabilities in its first release. In this blog post, we share the details of using DeepSeek R1 to build Retrieval-Augmented Generatio...

The purpose of this paper is to explain in detail the basic concepts, overall process, and key techniques of Embedding fine-tuning from multiple perspectives, and to explore its practical utility in the legal domain. Through this paper, readers will understand how to utilize specialized data in the legal domain to pre-trained Embedding models for ...

Recently, when I was choosing a data processing tool for the RAG knowledge base for my smart customer service project, I took a fresh look at the current mainstream document processing projects, including olmOCR, Marker, MinerU, Docling, Markitdown, Llamaparse...

Abstract Well-designed prompts are essential to enhance the reasoning capabilities of large language models (LLMs) while aligning their outputs with the task requirements of different domains. However, manually designing hints requires expertise and iterative experimentation. Existing hint optimization methods aim to automate this process, but they are strictly ...