6 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.CL2024★ 6 cited
Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models
Scott Barnett, Zac Brannelly, Stefanus Kurniawan +1
Large Language Models (LLMs) have the unique capability to understand and generate human-like text from input queries. When fine-tuned, these models show enhanced performance on do…
cs.SE2023
MLGuard: Defend Your Machine Learning Model!
Sheng Wong, Scott Barnett, Jessica Rivera-Villicana +4
Machine Learning (ML) is used in critical highly regulated and high-stakes fields such as finance, medicine, and transportation. The correctness of these ML applications is importa…