5 citations · 5 across the 3 of their papers we have counts for
5 papers
Enhancing Mixture-of-Experts Specialization via Cluster-Aware Upcycling
Sanghyeok Chu, Pyunghwan Ahn, Gwangmo Song +3
Sparse Upcycling provides an efficient way to initialize a Mixture-of-Experts (MoE) model from pretrained dense weights instead of training from scratch. However, since all experts…
Pri4R: Learning World Dynamics for Vision-Language-Action Models with Privileged 4D Representation
Jisoo Kim, Jungbin Cho, Sanghyeok Chu +9
Humans learn not only how their bodies move, but also how the surrounding world responds to their actions. In contrast, while recent Vision-Language-Action (VLA) models exhibit imp…
Beyond the Ground Truth: Enhanced Supervision for Image Restoration
Donghun Ryou, Inju Ha, Sanghyeok Chu +1
Deep learning-based image restoration has achieved significant success. However, when addressing real-world degradations, model performance is limited by the quality of groundtruth…
Fine-Grained Captioning of Long Videos through Scene Graph Consolidation
Sanghyeok Chu, Seonguk Seo, Bohyung Han
Recent advances in vision-language models have led to impressive progress in caption generation for images and short video clips. However, these models remain constrained by their…
Learning Debiased and Disentangled Representations for Semantic Segmentation
Sanghyeok Chu, Dongwan Kim, Bohyung Han
Deep neural networks are susceptible to learn biased models with entangled feature representations, which may lead to subpar performances on various downstream tasks. This is parti…