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, which rely on keyword matching, NoLiMA is characterized by carefully designed questions and key messages that force...
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 the two dominant frameworks for building LLM applications, LangChain and LangGraph, and analyze their strengths and weaknesses,...
Enable Builder Smart Programming Mode, unlimited use of DeepSeek-R1 and DeepSeek-V3, smoother experience than the overseas version. Just enter the Chinese commands, even a novice programmer can write his own apps with zero threshold.
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 an AI system, and each has a unique and interrelated role to play. A deeper understanding of it...
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 (LRMs) already have the ability to perform safety checks, which...
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.com/deansaco/r1-reasoning-rag.git project by combining the DeepSeek...
In recent years, the field of Artificial Intelligence has made significant progress in its reasoning capabilities. After OpenAI demonstrated the powerful inference potential of large-scale language models (LLMs) last year, organizations such as Google DeepMind, Alibaba, DeepSeek, and Anthropic have been quick to follow suit, using reinforcement learning (RL) techniques to train...
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 capable of automating tasks, but also exhibit near-human reasoning capabilities. However, traditional MAS architectures are often accompanied by ...
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 the understanding barriers so as to...
Recently, the terms Autonomous AI (AI), AI Agents, and Agents have been popping up a lot. Frankly, despite being data analysts and scientists, industry players have been a bit resistant to these AI-related trends and buzzwords in the past...
In recent years, Artificial Intelligence (AI) technologies have triggered a profound change in the field of programming. From v0 and bolt.new to programming tools that integrate Agent technology such as Cursor and Windsurf, AI Coding shows great potential to play a key role in the software development process, especially in rapid proto...
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 will analyze Artifact from theoretical concepts to practical implementation....
Recently in the intelligent customer service project to choose the RAG knowledge base of data processing tools, it re-looked at the current mainstream document processing projects, including olmOCR, Marker, MinerU, Docling, Markitdown, Llamaparse the 6 tools, and a brief comparison of them. A comprehensive view of the ...
DeepSeek R1 has demonstrated strong inference capabilities in its first release. In this blog post, we share in detail our experience using DeepSeek R1 to build a Retrieval-Augmented Generation (RAG) system, specifically for the legal document domain. We chose ...
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 role in the legal domain. Through this paper, readers will understand how to fine-tune pre-trained Embedding models using specialized data in the legal domain, so as to enhance the legal...
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 heavily ...
It's only February, and Deep Search is already looming as the new search standard for 2025. Giants like Google and OpenAI have unveiled their "Deep Research" products in an effort to capitalize on this wave of technology. (We're proud to be releasing our...
By Krish Maniar and William Fu-Hinthorn When writing cue words, we try to communicate our intentions to Large Language Models (LLMs) so that they can apply these instructions on complex data. However, it is not easy to clearly express all the nuances at once. Prompts are usually engineered by hand ...
This diagram clearly depicts the architectural blueprint of a modern, complex Question Answering (QA) or Retrieval-Augmented Generation (RAG) system. It begins with the user asking the question and continues through the final generation of the answer, showing in detail the intermediate...
At the center of the wave of artificial intelligence, AI Agent (Intelligent Body) is evolving at an amazing speed, just like the intelligent assistants coming out of sci-fi movies, quietly penetrating into every corner of the enterprise. They are no longer unattainable future concepts, but the secret weapon for enterprises to improve efficiency, optimize processes, and win in the market. 2...