Low-rank additive experts with dual-scale gating and threat-guided diversification improve multi-perturbation adversarial robustness by routing different threat types through distinct model pathways.
In: ICLR (2019)
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Counterfactual stress testing with causal generative models offers a more accurate proxy than simple perturbations for predicting medical image model performance under distribution shifts.
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RoME: Robust Mixture of Low-Rank Experts against Multiple Adversarial Perturbations
Low-rank additive experts with dual-scale gating and threat-guided diversification improve multi-perturbation adversarial robustness by routing different threat types through distinct model pathways.
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Counterfactual Stress Testing for Image Classification Models
Counterfactual stress testing with causal generative models offers a more accurate proxy than simple perturbations for predicting medical image model performance under distribution shifts.