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cs.CR2026
Sublinear Risk-Limiting Audits from Direct Ballot Selection and Statistical Ballot Manifests
Benjamin Fuller, Abigail Harrison, Alexander Russell
Risk-limiting audits (RLAs) rigorously guarantee a specified maximum probability that an incorrect electoral outcome will not be detected. Efficient RLA methods require a software-…
cs.LG2026
Analyzing Physical Adversarial Example Threats to Machine Learning in Election Systems
Khaleque Md Aashiq Kamal, Surya Eada, Aayushi Verma +4
Developments in the machine learning voting domain have shown both promising results and risks. Trained models perform well on ballot classification tasks (> 99% accuracy) but are…