Results 161 to 170 of about 3,227,651 (213)

OFFLINETender: Intelligent Extraction of Structured Data from Public Procurement and Tender Documents using Large Language Models and Retrieval-Augmented Generation

reservedPer le piccole e medie imprese (PMI) partecipare ai bandi di gara pubblici è diventato sempre più complesso: le informazioni sono frammentate su documenti diversi, pubblicate in formati eterogenei e spesso prive di notifiche tempestive ...
PIRON, MATTEO
core  

TCM-CoT-RAG: a chain-of-thought enhanced retrieval-augmented generation system for clinical decision support in Traditional Chinese Medicine rheumatology. [PDF]

Front Pharmacol
Fan B, Fang Y, Wang Z, Ma F.
europepmc   +1 more source

DentalEdu-AI graph: mapping evidence-grounded and knowledge-structured AI for dental education, assessment, and accuracy. [PDF]

Saudi Dent J
Yadalam PK, Karobari MI.
europepmc   +1 more source

Retrieval-Augmented Generation systems

Retrieval-Augmented Generation (RAG) systems combine information retrieval with large language model generation. They have become important because large language models can produce fluent answers while still su!ering from outdated knowledge ...
Fadakar, Melina
core  

Resource-efficient retrieval-augmented question answering for the Indian Lok Sabha dataset. [PDF]

Front Artif Intell
Sivakumar S, Meenakshi SP.
europepmc   +1 more source

Knowledge-enhanced large language model construction for garlic cultivation using GraphRAG. [PDF]

Front Plant Sci
Zhou K, Dong M, Meng X, Lv J, Long X, Hou R, Li Y, Hou J.   +7 more
europepmc   +1 more source

Self-adaptive Multimodal Retrieval-Augmented Generation

Traditional Retrieval-Augmented Generation (RAG) methods are limited by their reliance on a fixed number of retrieved documents, often resulting in incomplete or noisy information that undermines task performance.
Zhai, Wenjia
core  

Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language Models

Iterative retrieval refers to the process in which the model continuously queries the retriever during generation to enhance the relevance of the retrieved knowledge, thereby improving the performance of Retrieval-Augmented Generation (RAG).
Yu, Tian, Feng, Yang, Zhang, Shaolei
core  

Clinical Laboratory Terminology Standardization for Semantic Interoperability Using a Large Language Model-Based Agent: Methodological Study. [PDF]

J Med Internet Res
Wu L, Huang J, Wang H, Mai L, Zhan X, He X, Zhang X, Liang H, Li X, Bellou A.   +9 more
europepmc   +1 more source