Fine-Tuning Security Datasets Enhances Cross-Domain Robustness in Llama3 and DeepSeek R1

This report synthesises findings from 15 peer-reviewed papers addressing the following research question: How does fine-tuning on security-specific datasets impact the cross-domain robustness of Llama3 and Deepseek R1 in vulnerability classification tasks. 12 claims were extracted from source literature; 9 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 7.6/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: How does fine-tuning on security-specific datasets impact the cross-domain robustness of Llama3 and Deepseek R1 in vulnerability classification tasks?

Autonomous literature synthesis. Automated review score: 7.6/10. Full text and citation available at Assignee Research.