Skip to content
DraconiticResearch
Search Sources API
203,952 studies31 sourcesUpdated 10 min ago
Peer-reviewedCC BY 4.0Scientific Reports

Design and analysis of an intelligent audit risk assessment system based on retrieval-augmented large language model

Related

  1. GEO-BERT: A Retrieval augmented LLM Framework for Intelligent Dataset Retrieval from the Gene Expression Omnibus
    Maruf Islam Shuvo, Monjura Afrin Rumi, Naznin Akhter +3
    bioRxivPreprintAll rights reservedFull textBioinformatics & computational biologybioRxivPMC
  2. AFP assistant: a retrieval-augmented generation and large language model-powered multilingual polio chatbot for low-resource language communities
    Gelane Biru, Honey Gemechu, Firanol Teshome +8
    npj Digital MedicinePeer-reviewedCC BYFull text1 citedEpidemiology & public healthDOAJ
  3. Evaluating Retrieval-Augmented Generation for Industrial Cybersecurity Compliance Assessment
    Muhammad Ali Arshad
    ZenodoPreprintCC BY 4.0Full textZenodo
  4. Evidence-based clinical question answering using retrieval-augmented generation (RAG) and open-source large language models
    Ayesha Qasim, Jesus Jaime Moreno Escobar, Christian E. Maldonado-Sifuentes +3
    Scientific ReportsPeer-reviewedCC BY 4.0Full textEpidemiology & public healthCrossref
  5. Retrieval-Augmented Generation for Urdu Islamic Jurisprudence: A Review of Design Choices and a Reference Architecture
    Abis Hussain
    ZenodoPreprintCC BY 4.0Full textZenodo
BibTeX
@article{wang2026design,
  title = {{Design and analysis of an intelligent audit risk assessment system based on retrieval-augmented large language model}},
  author = {Jiayi Wang},
  journal = {Scientific Reports},
  year = {2026},
  month = nov,
  doi = {10.1038/s41598-026-79812-4},
  url = {https://www.nature.com/articles/s41598-026-79812-4},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Design and analysis of an intelligent audit risk assessment system based on retrieval-augmented large language model
AU  - Jiayi Wang
PY  - 2026
DA  - 2026/11/09
JO  - Scientific Reports
DO  - 10.1038/s41598-026-79812-4
UR  - https://www.nature.com/articles/s41598-026-79812-4
SN  - 2045-2322
ER  -