Scaling Effects on Vulnerability Classification in Llama3 Codestral and DeepSeek R1
Description
This report synthesises findings from 4 peer-reviewed papers addressing the following research question: To what extent do Llama3, Codestral, and Deepseek R1 maintain vulnerability classification performance when scaled to larger model sizes, as measured by accuracy and inference latency on the filtered. 5 claims were extracted from source literature; 5 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.5/10. This report is a machine-generated literature synthesis and does not constitute original research.
Research goal: To what extent do Llama3, Codestral, and Deepseek R1 maintain vulnerability classification performance when scaled to larger model sizes, as measured by accuracy and inference latency on the filtered Big-Vul dataset?
Autonomous literature synthesis. Automated review score: 8.5/10. Full text and citation available at Assignee Research.
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