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cs.LG2026
REPLICANT: Learning Policies for Evading and Hardening Malware Detectors
Shae McFadden, Ilias Tsingenopoulos, Mario D'Onghia +5
To determine the real-world effectiveness of machine learning based malware detection, it is vital to evaluate its robustness against highly capable adversaries. However, state-of-…
cs.LG2026
Reading Calibrated Uncertainty from Language Model Trajectories
Aliai Eusebi, Alexander Herzog, Xiaoyu Liang +3
The maximum softmax probability (MSP) represents a default approach when evaluating uncertainty quantification for language model generation with structured output. Although cheap,…