Sama-418 -

We evaluated SAMA-418 on image classification tasks using the CIFAR-10 and ImageNet datasets with ResNet-50 and Vision Transformer (ViT) architectures.

While effective, the rigid dependency on fixed $\beta$ values is a known limitation. sama-418

J. Liang, A. Patel, M. Sharma, K. Lee Affiliation: Sound and Music Analysis Lab (SAMA), Department of Electrical and Computer Engineering, University of Texas at Austin Conference Submission: ICASSP 2026 / NeurIPS Datasets and Benchmarks Track We evaluated SAMA-418 on image classification tasks using

Standard EMA-based optimizers update the first moment $m_t$ and second moment $v_t$ as: $$ m_t = \beta_1 m_t-1 + (1 - \beta_1) g_t $$ $$ v_t = \beta_2 v_t-1 + (1 - \beta_2) g_t^2 $$ Department of Electrical and Computer Engineering

Results from technical database logs indicate that SAMA-418 is frequently categorized as "Uncensored."