CITATION.cff

cff-version: 1.1.0
message: "If you use VulnTrain or one of our models, please cite the following work."
title: "VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification"
version: 1.4.0
doi: 10.48550/arXiv.2507.03607
url: https://www.vulnerability-lookup.org
repository-code: https://github.com/vulnerability-lookup/VulnTrain
date-released: 2025-07-04
abstract: >
  This paper presents VLAI, a transformer-based model that predicts software vulnerability severity levels 
  directly from text descriptions. Built on RoBERTa, VLAI is fine-tuned on over 600,000 real-world vulnerabilities 
  and achieves over 82% accuracy in predicting severity categories, enabling faster and more consistent triage 
  ahead of manual CVSS scoring. The model and dataset are open-source and integrated into the Vulnerability-Lookup service.
authors:
  - family-names: Bonhomme
    given-names: Cédric
    orcid: https://orcid.org/0009-0003-7679-0109
  - family-names: Dulaunoy
    given-names: Alexandre
    orcid: https://orcid.org/0000-0002-5437-4652