Results 51 to 60 of about 3,238,639 (146)

Medical LLMs: Fine-Tuning vs. Retrieval-Augmented Generation

Bioengineering
Large language models (LLMs) are trained on huge datasets, which allow them to answer questions from various domains. However, their expertise is confined to the data that they were trained on. In order to specialize LLMs in niche domains like healthcare,
Bhagyajit Pingua, Adyakanta Sahoo, Meenakshi Kandpal, Deepak Murmu, Jyotirmayee Rautaray, Rabindra Kumar Barik, Manob Jyoti Saikia   +6 more
doaj   +1 more source

GraphTrace: A Modular Retrieval Framework Combining Knowledge Graphs and Large Language Models for Multi-Hop Question Answering

Computers
This paper introduces GraphTrace, a novel retrieval framework that integrates a domain-specific knowledge graph (KG) with a large language model (LLM) to improve information retrieval for complex, multi-hop queries.
Anna Osipjan, Hanieh Khorashadizadeh, Akasha-Leonie Kessel, Sven Groppe, Jinghua Groppe   +4 more
doaj   +1 more source

Efficient retrieval-augmented generation [PDF]

Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo termsThe student, Ziyi Chen, accepted the attached license on 2024-04-28 at 15:42.The student, Ziyi Chen ...
Chen, Ziyi
core  

FictionRAG: A Stateful Metacognitive Framework for High-Fidelity Long-Narrative Role-Playing

Algorithms
Maintaining high-fidelity character personas and tracking trusted narrative facts remain significant challenges for LLM-based role-playing systems, particularly in long-context scenarios. Traditional Retrieval-Augmented Generation (RAG) approaches, which
Yifei Deng, Yudong Zhang, Jingpu Yang, Miao Fang   +3 more
doaj   +1 more source

KAQG: A Knowledge-Graph-Enhanced RAG for Difficulty-Controlled Question Generation

IEEE Access
This study introduces Knowledge Augmented Question Generation (KAQG), an educational assessment framework that integrates Item Response Theory (IRT), Bloom’s Taxonomy, and knowledge graphs into a multi-agent Retrieval-Augmented Generation (RAG ...
Ching Han Chen, Ming Fang Shiu
doaj   +1 more source

GraphRAG-Enabled Local Large Language Model for Gestational Diabetes Mellitus: Development of a Proof-of-Concept

JMIR Diabetes
BackgroundGestational diabetes mellitus (GDM) is a prevalent chronic condition that affects maternal and fetal health outcomes worldwide, increasingly in underserved populations.
Edmund Evangelista, Fathima Ruba, Salman Bukhari, Amril Nazir, Ravishankar Sharma   +4 more
doaj   +1 more source

A Comparative Evaluation of RAG Architectures for Cross-Domain LLM Applications: Design, Implementation, and Assessment

IEEE Access
Retrieval-Augmented Generation (RAG) pairs large language models with external search to constrain knowledge staleness and hallucination, a critical need in finance and e-commerce where numerical precision and regulatory auditability are non-negotiable ...
Pinar Ersoy, Mustafa Ersahin
doaj   +1 more source

Development of a Retrieval-Augmented Generation (RAG) Chatbot [PDF]

Ovidius University Annals: Economic Sciences Series
Our research presents a Retrieval-Augmented Generation (RAG) chatbot designed for intelligent document-based question answering. Built with Streamlit as the front-end, the application integrates LLaMA2 models hosted on Replicate, alongside a document ...
Simona-Vasilica Oprea , Adela Bâra
doaj  

Enhancing Corporate Information Retrieval: Sensitivity Analysis in Retrieval-Augmented Generation Applications

LAUREA MAGISTRALEQuesta tesi esamina come migliorare il reperimento delle informazioni aziendali utilizzando l’analisi della sensibilità nelle applicazioni di Retrieval-Augmented Generation (RAG).
MARRONE, TIZIANO
core  

retrieval augmented generation: one bounded, context-dependent signal across receipts

Researka accepted publication: 5c993ba1-5ebb-4a12-b4dc-a4fe2418a927 Source submission: 5e31a86d-9e6a-499c-80d8-e1e5c020abe3 retrieval augmented generation: Bounded signal: retrieval augmented generation is only a source-level context map; the selected ...
Dominic Lynch
core   +1 more source