Large Language Models

Detailed Explanation of LlamaIndex Workflows: Key to Improving Data Processing Efficiency

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Detailed Explanation of LlamaIndex Workflows: Key to Improving Data Processing Efficiency

Click the “Blue Words” to Follow Us LlamaIndex, as a powerful framework, provides a solid foundation for building data pipelines that connect with large language models (LLMs). It implements a modular approach to query execution through structured workflows, simplifying solutions to complex problems. Today, let’s discuss the workflows of LlamaIndex. 1. Basics of LlamaIndex Workflows … Read more

Simplifying Complexity: Principles for Building Efficient and Reliable AI Agents

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Simplifying Complexity: Principles for Building Efficient and Reliable AI Agents

Definition of AI Agent When it comes to agents, many people think it is a product of LLMs, but that is not the case. The modern definition of AI agents has gradually formed alongside the development of AI since the 1950s. Its roots can be traced back to earlier philosophical thoughts and scientific explorations. In … Read more

Comparing Mistral AI and Meta: Top Open Source LLMs

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Comparing Mistral AI and Meta: Top Open Source LLMs

Source: Deephub Imba This article is about 5000 words long, and it is recommended to read for 10 minutes. This article will compare Mistral 7B vs Llama 2 7B and Mixtral 8x7B vs Llama 2 70B. To improve performance, large language models (LLMs) typically achieve this goal by increasing the model size. This article will … Read more

Pinecone and LangChain: Powerful Tools for LLM Application Development

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Pinecone and LangChain: Powerful Tools for LLM Application Development

To avoid losing contact, please also follow the backup account. Large language models are machine learning models capable of generating natural language text based on context. In recent years, with the development of deep learning and big data, the performance and capabilities of language models have significantly improved, leading to the emergence of many applications … Read more

Chronos: Slow Thinking RAG Technology for News Timeline Summarization

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Chronos: Slow Thinking RAG Technology for News Timeline Summarization

Paper: https://arxiv.org/abs/2501.00888 Github: https://github.com/Alibaba-NLP/CHRONOS Demo: https://modelscope.cn/studios/vickywu1022/CHRONOS In the digital age, the exponential growth of news information makes it crucial to extract and organize historical event timelines from massive texts. To address this challenge, Alibaba’s Tongyi Lab and researchers from Shanghai Jiao Tong University proposed a new framework for news timeline summarization based on agents—CHRONOS, named … Read more

Goodbye Large Models: MiniRAG for Efficient Knowledge Retrieval

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Goodbye Large Models: MiniRAG for Efficient Knowledge Retrieval

Today, I will share a retrieval-augmented generation method designed for resource-constrained scenarios: MiniRAG. Paper link: https://arxiv.org/pdf/2501.06713 Code link: https://github.com/HKUDS/MiniRAG Introduction With the rapid development of retrieval-augmented generation (RAG) technology, the performance of language models in knowledge retrieval and generation tasks has significantly improved. However, existing methods heavily rely on large language models (LLMs), leading to … Read more

AutoPrompt: Automatically Generated Prompts for Language Models

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AutoPrompt: Automatically Generated Prompts for Language Models

Paper Title “AUTOPROMPT: Eliciting Knowledge from Language Models with Automatically Generated Prompts”, authored by Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, and Sameer Singh. The paper was published at the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). The paper aims to enhance the performance of language models on downstream … Read more

Common Design Pitfalls in Prompt Engineering

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Common Design Pitfalls in Prompt Engineering

Hello everyone, I am Xiaoshui! Today, I want to share my learning notes from the AI learning course “Everyone is a Prompt Engineer” by Geek Time, focusing on common design pitfalls in prompts. Now, let me share my experiences regarding some of the above pitfalls when using AI large language models. As a programmer, my … Read more

In-Depth Analysis of Word2Vec Principles

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In-Depth Analysis of Word2Vec Principles

Follow the public account “ML_NLP” Set as “Starred”, heavy content delivered first time! Overview of this article: 1. Background Knowledge Word2Vec is a type of language model that learns semantic knowledge from a large amount of text data in an unsupervised manner, and is widely used in natural language processing. Word2Vec is a tool for … Read more

OpenRouter: Unified Access to Large Language Models

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OpenRouter: Unified Access to Large Language Models

OpenRouter is an impressive free AI tool. When we develop using APIs from closed-source models like OpenAI and Claude, as well as open-source models like LLaMa, we often encounter differences among different vendors’ APIs. Therefore, when switching between different large model service providers, your code typically requires modifications. The purpose of OpenRouter is to encapsulate … Read more