Author

Sheng-Yun Peng

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Jul 2026

ALLUDE: A Unified Evaluation System for Configurable Attacks in Differentiable Environments

Through ALLUDE's end-to-end differentiable rendering, adversarial attacks can be optimized against shifting real-world deployment conditions, and can be optimized against shifting real-world deployment conditions.

Mansi Phute, Alexander D. Greenhalgh, Matthew Hull et al. · arXiv.org · 0 citations

#machine learning Preprint Aug 2026

ARMOR: Manifold-Oriented Training for Adversarially Robust Aerial Object Detection under Data Scarcity

Adversarial Robustness with Manifold-Oriented Training (ARMOR), a novel defense that realizes the core insights of on-manifold adversarial training (OMAT) in low-data regimes and translates insights from manifold-based training to defend object detectors amidst training data scarcity.

Hao-Ran Wang, Matthew Lau, Alec Helbling et al. · 0 citations