AI Fundamentals

 

  • Machine Learning
  • Deep Learning
  • Neural Networks
  • Natural Language Processing (NLP)
  • Computer Vision
  • Reinforcement Learning

New Insights from Academician E Wei Nan: Memory3 in Large Models

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New Insights from Academician E Wei Nan: Memory3 in Large Models

MLNLP community is a well-known machine learning and natural language processing community, covering NLP graduate students, university teachers, and corporate researchers both domestically and internationally. 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 the progress of beginners. … Read more

Multi-Head RAG: Multi-Head Attention Activation Layer for Document Retrieval

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Multi-Head RAG: Multi-Head Attention Activation Layer for Document Retrieval

Source: DeepHub IMBA This article is about 2500 words long and suggests a reading time of 9 minutes. This paper proposes a new scheme that utilizes the multi-head attention layer of the decoder model instead of the traditional feed-forward layer activation. The existing RAG solutions may suffer because the embeddings of the most relevant documents … Read more

Understanding Vector Distance in Vector Databases

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Understanding Vector Distance in Vector Databases

Vector distance is crucial in various fields such as mathematics, physics, engineering, and computer science. They are used to measure physical quantities, analyze data, identify similarities, and determine the relationships between vectors. This article provides an overview of vector distance and its applications in data science. What Is Vector Distance? Vector distance, also known as … Read more

Understanding Vector Database Distances: A Comprehensive Guide

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Understanding Vector Database Distances: A Comprehensive Guide

Vector distances are crucial in various fields such as mathematics, physics, engineering, and computer science. They are used to measure physical quantities, analyze data, identify similarities, and determine relationships between vectors. This article will provide an overview of vector distances and their applications in data science. What Is Vector Distance? Vector distance, also known as … Read more

Professor E Wei Nan’s New Work: Memory3 in Large Models

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Professor E Wei Nan's New Work: Memory3 in Large Models

Reported by Machine Heart Editor: Chen Chen A 2.4B Memory3 outperforms larger LLM and RAG models. According to a message from the WeChat public account of Machine Heart: In recent years, large language models (LLMs) have gained unprecedented attention due to their extraordinary performance. However, the training and inference costs of LLMs are high, and … Read more

Visualizing FAISS Vector Space and Adjusting RAG Parameters to Improve Result Accuracy

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Visualizing FAISS Vector Space and Adjusting RAG Parameters to Improve Result Accuracy

Source: DeepHub IMBA This article is approximately 3600 words long, and it is recommended to read it in 7 minutes. In this article, we will use the visualization library renumics-spotlight to visualize the multi-dimensional embeddings of the FAISS vector space in 2-D, and explore the possibility of improving the accuracy of RAG responses by changing … Read more

Performance Improvement with Pseudo-Graph Indexing for RAG

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Performance Improvement with Pseudo-Graph Indexing for RAG

This article is approximately 5500 words long and is recommended for an 11-minute read. This paper proposes a pseudo-graph structure by relaxing the pattern constraints on data and relationships in traditional KGs. Paper Title: Empowering Large Language Models to Set up a Knowledge Retrieval Indexer via Self-Learning Author Affiliation: Renmin University of China (RUC), Shanghai … Read more

Enhancing RAG Capabilities with Knowledge Graphs to Reduce LLM Hallucinations

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Enhancing RAG Capabilities with Knowledge Graphs to Reduce LLM Hallucinations

Source: DeepHub IMBA This article is approximately 2600 words long and is recommended to be read in 8 minutes. For hallucinations in large language models (LLM), knowledge graphs have proven to be superior to vector databases. When using large language models (LLMs), hallucination is a common issue. LLMs generate fluent and coherent text but often … Read more

FaaF: A Custom Fact Recall Evaluation Framework for RAG Systems

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FaaF: A Custom Fact Recall Evaluation Framework for RAG Systems

Source: DeepHub IMBA This article is about 1000 words long and is recommended to read in 5 minutes. When real information exceeds a few words, the chance of exact matching becomes too slim. In RAG systems, actual fact recall evaluation may face the following issues: There has not been much attention paid to automatically verifying … Read more

ACL2024 | LLM+RAG May Destroy Information Retrieval: An In-Depth Study

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ACL2024 | LLM+RAG May Destroy Information Retrieval: An In-Depth Study

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 corporate researchers. The Vision of the Community is to promote communication and progress between the academic community, industry, and enthusiasts in machine learning and natural language processing, especially for beginners. … Read more