12 citations · 14 across the 14 of their papers we have counts for
6 papers · 1 filter
Weight Concentration Regularization for Improving Pruning Robustness Under High Sparsity
Vincent-Daniel Yun, Junhyuk Jo, Sunwoo Lee
Deep neural networks achieve outstanding performance across vision and language tasks, yet their large parameter counts limit deployment in resource-constrained settings. One-shot…
MedCLM: Learning to Localize and Reason via a CoT-Curriculum in Medical Vision-Language Models
Soo Yong Kim, Suin Cho, Vincent-Daniel Yun +1
Bridging clinical diagnostic reasoning with AI remains a central challenge in medical imaging. We introduce MedCLM, an automated pipeline that converts detection datasets into larg…
Insights from Gradient Dynamics: Gradient Autoscaled Normalization
Vincent-Daniel Yun
Gradient dynamics play a central role in determining the stability and generalization of deep neural networks. In this work, we provide an empirical analysis of how variance and st…
Why Does Stochastic Gradient Descent Slow Down in Low-Precision Training?
Vincent-Daniel Yun
Low-precision training has become crucial for reducing the computational and memory costs of large-scale deep learning. However, quantizing gradients introduces magnitude shrinkage…
Fast Fourier Transform-Based Spectral and Temporal Gradient Filtering for Differential Privacy
Hyeju Shin, Vincent-Daniel, Kyudan Jung +1
Differential Privacy (DP) has emerged as a key framework for protecting sensitive data in machine learning, but standard DP-SGD often suffers from significant accuracy loss due to…
Sharpness-Aware Minimization with Z-Score Gradient Filtering
Vincent-Daniel Yun
Deep neural networks achieve high performance across many domains but can still face challenges in generalization when optimization is influenced by small or noisy gradient compone…