VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification

Cédric, Alexandre Dulaunoy

VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification: 8 upvotes on Hugging Face Daily Papers, #23 of 27 papers on 2025-07-08. Day-by-day upvote history.

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.

Paper page on Hugging Face · arXiv

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