LLM Fine-Tuning · Cybersecurity
Researched instruction fine-tuning of LLMs for cybersecurity applications.
During this research internship, I explored the applications of Large Language Models (LLMs) in cybersecurity, with a focus on instruction fine-tuning. The goal was to fine-tune an existing LLM and compare its performance to its non fine-tuned counterpart to assess the impact of fine-tuning.
Our approach was loosely based on the method proposed by Levi et al. (2024).
By the end of the internship, the fine-tuned model showed the approach was feasible, though it did not clearly outperform the non fine-tuned baseline. These results may have looked different with more time, so as my internship came to an end, the project was handed off to someone else to continue.