Vincent-Daniel Yun
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Publications
E-AI Project
CV
한국어
Publications
* denotes equal contribution.
Selected
Model Compression
Agent
Optimization
Others
Selected Publications
Ghosted Layers: Unconstrained Activation Alignment for Recovering Layer-Pruned LLMs
VD Yun
, J Jo, SP Karimireddy, S Lee
Under Review
Preprint (arXiv), 2026
Paper
Robust Multi-Agent LLMs under Byzantine Faults
H Lee*,
VD Yun*
, H Oh*, D Panagou, SP Karimireddy
Workshop
ICML 2026 · Agents in the Wild: Safety, Security, and Beyond
Revisiting 16-bit Neural Network Training: A Practical Approach for Resource-Limited Learning
J Yun
, S Choi, F Rameau, B Kang, Z Fu
Conference
ICONIP 2025 · 🥇 Best Paper Award
Paper
Model Compression
Locality-Aware Redundancy Pruning for LLM Depth Compression
VD Yun*
, Y Kim*, W Lim*, YJ Heo, M Kim, S Lee
Under Review
2026
Rethinking Layer Redundancy: Calibration Matters More Than Search in LLM Depth Pruning
M Kim*,
VD Yun*
, Y Kim*, S Cho, W Lim, S Lee
Under Review
2026
Ghosted Layers: Unconstrained Activation Alignment for Recovering Layer-Pruned LLMs
VD Yun
, J Jo, SP Karimireddy, S Lee
Under Review
Preprint (arXiv), 2026
Paper
Spectrum-Shaping Regularization for Neural Network Training Robust to Low-Rank Pruning
J Jo,
VD Yun
, S Lee
Under Review
2026
Weight Concentration Regularization for Improving Pruning Robustness Under High Sparsity
VD Yun
, J Jo, S Lee
Under Review
2026
Revisiting 16-bit Neural Network Training: A Practical Approach for Resource-Limited Learning
J Yun
, S Choi, F Rameau, B Kang, Z Fu
Conference
ICONIP 2025 · 🥇 Best Paper Award
Paper
Robust Neural Pruning with Gradient Sampling Optimization for Residual Neural Networks
J Yun
Conference
IJCNN 2024 · Oral
Paper
Agent
Robust Multi-Agent LLMs under Byzantine Faults
H Lee*,
VD Yun*
, H Oh*, D Panagou, SP Karimireddy
Workshop
ICML 2026 · Agents in the Wild: Safety, Security, and Beyond
Optimization
Sharpness-Aware Minimization with Z-Score Gradient Filtering
VD Yun
Conference
IEEE ICASSP 2026 · also at NeurIPS 2025 OPT
Paper
Conference
On How Muon Reshapes Skill Learning Dynamics
AR Aranda,
VD Yun
, V Sharan, B Vasudeva
Workshop
ICML 2026 · High-dimensional Learning Dynamics (HiLD)
Asynchronous Sharpness-Aware Minimization for Fast and Accurate Deep Learning
J Jo, J Lim,
VD Yun
, S Lee
Under Review
2026
Why Does Stochastic Gradient Descent Slow Down in Low-Precision Training?
VD Yun
Workshop
NeurIPS 2025 · OPT
Paper
Workshop
Hyperparameter-Free Auto-Scaled Gradient Normalization via Global Standard Deviation Dynamics
VD Yun
Workshop
NeurIPS 2025 · OPT
Paper
Workshop
Fast Fourier Transform-Based Spectral and Temporal Gradient Filtering for Differential Privacy
H Shin*,
VD Yun*
, K Jung*, S Yun*
Workshop
ACM CIKM 2025 · Human-Centric AI
Paper
Workshop
Stochastic Gradient Sampling for Enhancing Neural Networks Training
J Yun
Journal
Neural Computing and Applications, 2025
ZNorm: Z-Score Gradient Normalization Accelerating Skip-Connected Network Training Without Architectural Modification
J Yun
Workshop
AAAI 2025 · AI for Research and Scalable, Efficient Systems
Paper
Workshop
Mitigating Gradient Overlap in Deep Residual Networks with Gradient Normalization for Improved Non-Convex Optimization
J Yun
Workshop
IEEE BigData 2024 · BPOD
Paper
Workshop
Others
MedCLM: Learning to Localize and Reason via a CoT-Curriculum in Medical Vision-Language Models
VD Yun
, et al.
Under Review
Preprint (arXiv)
Paper
Merging Multiple Independently Trained Neural Networks Based on Genetic Algorithm
D Yun
arXiv
Preprint, 2024
Extreme Solar Flare Prediction Using Residual Networks with HMI Magnetograms and Intensitygrams
J Yun
, J Shin
arXiv
Preprint, 2024
Analysis and Predictive Modeling of Solar Coronal Holes Using Computer Vision and ARIMA-LSTM Networks
J Yun
, J Shin
Conference
SPAICE 2024 · ESA / IAA, AI in and for Space
Paper
Conference
Uncertainty Estimation for Tumor Prediction with Unlabeled Data
J Yun
, S Abousamra, C Li, R Gupta, T Kurc, D Samaras, A Van Dyke, et al.
Workshop
IEEE/CVF CVPR 2024 · CVMI
Paper