1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.AR2026
APT: Accelerating Diffusion Transformers via Attention Probability-Guided Pruning and Quantization
Sungyeob Yoo, Seeyeon Kim, Joonyong Park +2
Recent advances in generative AI have significantly increased the demand for high-resolution image and video generation, positioning diffusion models as a core technology. Among th…
cond-mat.mtrl-sci2026
Multimodal Transformer for Sample-Aware Prediction of Metal-Organic Framework Properties
Seunghee Han, Jaewoong Lee, Jihan Kim
Metal-organic frameworks (MOFs) are a major target of machine-learning-based property prediction, yet most models assume that a single framework representation maps to a single pro…
cs.AR2025★ 1 cited
LightNobel: Improving Sequence Length Limitation in Protein Structure Prediction Model via Adaptive Activation Quantization
Seunghee Han, Soongyu Choi, Joo-Young Kim
Recent advances in Protein Structure Prediction Models (PPMs), such as AlphaFold2 and ESMFold, have revolutionized computational biology by achieving unprecedented accuracy in pred…