GitHub16 天
Security: skywarth/document-embeddings
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GitHub4 天
Security: daniyalb/Document-Search-with-Embeddings
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Revolutionizing Medical Knowledge Retrieval Through Advanced Matching Technology
Most document retrieval in GenAI is based on semantic similarity, but this approach falls short in a few ways when analyzing clinical texts.
marktechpost27 天
Building a Retrieval-Augmented Generation (RAG) System with DeepSeek R1: A Step-by-Step Guide
To enable efficient retrieval of relevant documents, you can use a vector store like FAISS (Facebook AI Similarity Search). This involves generating embeddings for your documents. Here’s how to ...
IEEE2 天
Optimizing Pre-Trained Code Embeddings With Triplet Loss for Code Smell Detection
Abstract: Code embedding represents code semantics in vector form. Although code embedding-based systems have been successfully applied to various source code analysis tasks, further research is ...
IEEE11 天
CoLLM: Integrating Collaborative Embeddings Into Large Language Models for Recommendation
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=69 ...
Amazing Innovation in AI and Enterprise Solutions by Lakshman Kumar Jamili
Lakshman Kumar Jamili is a distinguished Lead Gen AI Architect based in Prosper, Texas, with over 12 years of experience in software development and AI solutions.
Statetechmagazine9 天
What Is Retrieval Augmented Generation, and How Are State and Local Agencies Using It?
RAG allows government agencies to infuse generative artificial intelligence models and tools with up-to-date information, ...
Computer Weekly6 天
RAG AI: ‘Do it yourself,’ says NYC data scientist
New York City council data scientist says organisations should get their hands dirty with open source AI as his teams build ...