RLVR exhibits correct-set turnover where solved problems regress during training, and a periodic review mechanism exploiting a repair-window principle improves retention and performance over baselines.
ExHuBERT: Enhancing
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SIGMA applies post-hoc XAI saliency maps to define reusable sparse masks for magnitude-bounded perturbations on self-supervised speech features, evaluated on IEMOCAP and TESS for competitive attack success with explanation consistency trade-offs.
citing papers explorer
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SIGMA: Saliency-Guided Sparse Mask Attacks for Speech Emotion Recognition
SIGMA applies post-hoc XAI saliency maps to define reusable sparse masks for magnitude-bounded perturbations on self-supervised speech features, evaluated on IEMOCAP and TESS for competitive attack success with explanation consistency trade-offs.