2 papers
cs.LG2026
Noisy but Valid: Robust Statistical Evaluation of LLMs with Imperfect Judges
Chen Feng, Minghe Shen, Ananth Balashankar +2
Reliable certification of Large Language Models (LLMs)-verifying that failure rates are below a safety threshold-is critical yet challenging. While "LLM-as-a-Judge" offers scalabil…
cs.LG2024
PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks
Chen Feng, Ziquan Liu, Zhuo Zhi +3
It is widely known that state-of-the-art machine learning models, including vision and language models, can be seriously compromised by adversarial perturbations. It is therefore i…