Unlocking new capabilities in large language models with MindMap: Integrating knowledge graphs for superior reasoning and accurate responses.
A paper review of MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models
Source: arxiv
Our method enables LLMs to comprehend KG inputs and infer with a combination of implicit and external…
Revolutionizing document integration with Docs2KG: transforming heterogeneous data into unified knowledge graphs.
A paper review of GraphRAG: Design Patterns, Challenges, and Recommendations
Source: arxiv
Project repo: github
Docs2KG introduces a novel framework to extract and unify information, including text, table, image etc. from various unstructured documents.
from the article
Overview
Docs2KG introduces a novel…
Combining knowledge graphs with retrieval-augmented generation for more accurate, contextually aware AI responses.
A paper review of GraphRAG: Design Patterns, Challenges, and Recommendations
Source: substack
GraphRAG represents a significant advancement in AI-driven knowledge retrieval by combining the strengths of knowledge graphs and retrieval-augmented generation.
from the article
Overview
This paper discusses GraphRAG, a…
A month ago, LlamaIndex announced the launch of LlamaCloud, a pioneering managed parsing, ingestion, and retrieval service aimed at enhancing production-grade context augmentation for LLM and RAG applications.
Key components of LlamaCloud include LlamaParse, a proprietary parsing tool for complex documents with embedded objects like tables and figures, which integrates seamlessly with LlamaIndex ingestion and retrieval. This integration enables…
In the last several decades, when people consider building a knowledge-related solution, they tend to look into two distinct directions based on whether data is structured or unstructured. Accordingly, there is the so-called structured search using a query language over a database or semantic search using inferencing and reasoning over the meaning of data, mostly…