Multi-Class vs. Multi-Label BERT for CVE-to-CWE Mapping: How Taxonomy Structure Shapes the Errors

arXiv:2607.07573 · cs.LG, cs.CR · Submitted 2026-07-08 · Read on arXiv

cs.LG, cs.CR

Submitted: 2026-07-08

Updated: 2026-07-08

Comments: 3 figures, 7 tables, to be published at the ICANN 2026 (International Conference on Artificial Neural Networks)

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 6× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Abstraction — 3× in this paper · explained in 1 episode
• Common Vulnerabilities and Exposures — 3× in this paper
• Adam — 2× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Assigning Common Weakness Enumeration — 2× in this paper
• Domain Adaptation — 2× in this paper · explained in 5 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Hierarchical Classification — 1× in this paper · explained in 2 episodes
• Ontology — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes

Sources

• RoBERTa: A Robustly Optimized BERT Pretraining Approach

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