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cs.LG2026
Information Theoretic Adversarial Training of Large Language Models
Yiwei Zhang, Jeremiah Birrell, Reza Ebrahimi +3
Large language models (LLMs) remain vulnerable to adversarial prompting despite advances in alignment and safety, often exhibiting harmful behaviors under novel attack strategies.…
cs.LG2024
Adversarial Domain Adaptation for Metal Cutting Sound Detection: Leveraging Abundant Lab Data for Scarce Industry Data
Mir Imtiaz Mostafiz, Eunseob Kim, Adrian Shuai Li +3
Cutting state monitoring in the milling process is crucial for improving manufacturing efficiency and tool life. Cutting sound detection using machine learning (ML) models, inspire…