Author

Alexander Herzog

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#artificial intelligence Preprint Oct 2026

U-Space: Uncovering When and Why Uncertainty Arises in Language Models

Large language models are informing decisions with ever-higher stakes. As the consequences of their errors grow, a central question becomes harder to ignore: how much can we trust an individual answer? Yet recognizing when to defer remains difficult because language models can present incorrect conclusions with fluent...

Tobias Braun, Nils Loose, Alexander Herzog et al. · 0 citations

#machine learning Preprint Aug 2026

REPLICANT: Learning Policies for Evading and Hardening Malware Detectors

This work presents Replicant, a deep reinforcement learning framework that learns the realistic task of evasion under a strict label-only black-box threat model and demonstrates that learning the task of evasion not only results in stronger attack performance but provides a better signal for hardening malware detectors...

Shae McFadden, Ilias Tsingenopoulos, Mario D'Onghia et al. · 0 citations