Knowledge Retrieval

ACL 2024: Cambridge Team Open Sources Pre-trained Multi-modal Retriever

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ACL 2024: Cambridge Team Open Sources Pre-trained Multi-modal Retriever

Follow our public account to discover the beauty of CV technology This article shares the ACL 2024 paper PreFLMR: Scaling Up Fine-Grained Late-Interaction Multi-modal Retrievers, open-sourced by the Cambridge University team, empowering multi-modal large model RAG applications, and is the first pre-trained general multi-modal late-interaction knowledge retriever. Paper link: https://arxiv.org/abs/2402.08327 Project homepage: https://preflmr.github.io/ Introduction The … 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

Forget RAG, Embrace Large Models

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Forget RAG, Embrace Large Models

“ Happy New Year! This article should be the last piece in the collection of algorithm insights regarding RAG. Throughout the past year, most of my work has focused on some aspects of large model applications, and I would like to briefly discuss two points that left a significant impression on me regarding RAG system … 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

RAG System: A Revolution in Real-Time Information Retrieval Driven by Large Models

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RAG System: A Revolution in Real-Time Information Retrieval Driven by Large Models

Abstract The RAG system is gradually revolutionizing our understanding of AI-driven information processing. To fully leverage its potential, understanding its fundamental principles is crucial. This article aims to succinctly analyze the RAG system, hoping to provide insights and resonance for readers. What is the RAG System? In short, the RAG system integrates large language models … Read more