7 citations · 9 across the 2 of their papers we have counts for
2 papers
cs.AI2025★ 2 cited
A Practical Guide for Evaluating LLMs and LLM-Reliant Systems
Ethan M. Rudd, Christopher Andrews, Philip Tully
Recent advances in generative AI have led to remarkable interest in using systems that rely on large language models (LLMs) for practical applications. However, meaningful evaluati…
cs.LG2022★ 7 cited
Transformers for End-to-End InfoSec Tasks: A Feasibility Study
Ethan M. Rudd, Mohammad Saidur Rahman, Philip Tully
In this paper, we assess the viability of transformer models in end-to-end InfoSec settings, in which no intermediate feature representations or processing steps occur outside the…