One of the most pressing challenges to the continued deployment of nuclear energy systems is in the ultimate management and disposition of discharged fuel assemblies. While reprocessing and recovery ...

Abstract: This paper presents a secure question answering framework for financial compliance using a graph-based retrieval-augmented generation (Graph-RAG) model. The system constructs a multi-layer ...

What if your AI agent could not only answer your questions but also truly understand them, navigating complex queries with precision and speed? While the rise of vector search has transformed how AI ...

Handling questions that involve both natural language and structured tables has become an essential task in building more intelligent and useful AI systems. These systems are often expected to process ...

Add a description, image, and links to the rag-framework topic page so that developers can more easily learn about it.

Though Retrieval-Augmented Generation has been hailed — and hyped — as the answer to generative AI's hallucinations and misfires, it has some flaws of its own. Retrieval-Augmented Generation (RAG) — a ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Receptor tyrosine kinases (RTKs) are key regulators of cellular signaling and are ...

Abstract: Large Language Models (LLMs) integrated with Retrieval-Augmented Generation (RAG) have significantly enhanced AI-driven knowledge synthesis by dynamically incorporating external sources.

DSA587F25_langchain/ ├── LangChain_tutorialDSA587F25.ipynb # Main tutorial notebook ├── lang_funcs.py # Utility functions ├── requirements.txt ...