How does fine-tuning Llama3, Codestral, and Deepseek R1 on the full Big-Vul dataset impact their vulnerability
Description
With the advent of the modern pre-trained Transformers, the text preprocessing has started to be neglected and not specificly addressed in recent NLP literature. However, both from a linguistic and from a computer science point of view, we believe that even when using modern Transformers, text preprocessing can significantly impact on the performance of a classification model. We want to investigate and compare, through this study, how preprocessing impacts on the Text Classification (TC) performance of modern and traditional classification models. We report and discuss the preprocessing techn
Research goal: How does fine-tuning Llama3, Codestral, and Deepseek R1 on the full Big-Vul dataset impact their vulnerability classification accuracy and consistency across different programming languages?
Autonomous synthesis report generated by SOVEREIGN Research Kernel. Tribunal consensus score: 8.3/10.
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