Publications_1 - National AI Research Lab

#Breakthrough in Neural Scaling Law

Active Prompt Learning with Vision-Language Model Priors

Year: 2025 / Author: Hoyoung Kim, Seokhee Jin, Changhwan Sung, Jaechang Kim, Jungseul Ok / Journal: TMLR

#Breakthrough in Neural Scaling Law

Retrieval-Augmented Generation with Estimation of Source Reliability

Year: 2025 / Author: Jeongyeon Hwang, Junyoung Park, Hyejin Park, Dongwoo Kim, Sangdon Park, Jungseul Ok / Conference: Conference on Empirical Methods in Natural Language Processing (EMNLP)

#Breakthrough in Neural Scaling Law

Adaptive Non-uniform Timestep Sampling for Accelerating Diffusion Model Training

Year: 2025 / Author: Myunsoo Kim, Donghyeon Ki, Seong-Woong Shim, Byung-Jun Lee / Conference: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

#Breakthrough in Neural Scaling Law

K/DA: Automated Data Generation Pipeline for Detoxifying Implicitly Offensive Language in Korean

Year: 2025 / Author: Minkyeong Jeon, Hyemin Jeong, Yerang Kim, Jiyoung Kim, Jae Hyeon Cho, Byung-Jun Lee / Conference: Annual Meeting of the Association for Computational Linguistics (ACL)

#Breakthrough in Neural Scaling Law

Iterative Prompt Refinement for Safer Text-to-Image Generation

Year: 2025 / Author: Jinwoo Jeon, JunHyeok Oh, Hayeong Lee, Byung-Jun Lee / Conference: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)

#Breakthrough in Neural Scaling Law

Rethinking DPO: The Role of Rejected Responses in Preference Misalignment

Year: 2025 / Author: Jay Hyeon Cho, JunHyeok Oh, Myunsoo Kim, Byung-Jun Lee / Conference: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)

#Breakthrough in Neural Scaling Law

NBDI: A Simple and Effective Termination Condition for Skill Extraction from Task-Agnostic Demonstrations

Year: 2025 / Author: Myunsoo Kim, Hayeong Lee, Seong-Woong Shim, JunHo Seo, Byung-Jun Lee / Conference: International Conference on Machine Learning (ICML)

#Breakthrough in Neural Scaling Law

Towards Generalizable 3D Human Pose Estimation via Ensembles on Flat Loss Landscapes

Year: 2025 / Author: Jumin Han, Jun-Hee Kim, Seong-Whan Lee / Conference: Conference on Neural Information Processing Systems (NeurIPS)

#Breakthrough in Neural Scaling Law

GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs

Year: 2025 / Author: Kun-Woo Kim, Ji-Hoon Park, Ju-Min Han, Seong-Whan Lee / Conference: International Joint Conference on Neural Networks (IJCNN)

#Breakthrough in Neural Scaling Law

Towards Fine-Grained Interpretability: Counterfactual Explanations for Misclassification with Saliency Partition

Year: 2025 / Author: Lintong Zhang, Kang Yin, Seong-Whan Lee / Conference: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

#Breakthrough in Neural Scaling Law

DiGIT: Multi-Dilated Gated Encoder and Central-Adjacent Region Integrated Decoder for Temporal Action Detection Transformer

Year: 2025 / Author: Ho-Joong Kim, Yearang Lee, Jung-Ho Hong, Seong-Whan Lee / Conference: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

#Breakthrough in Neural Scaling Law

Integrating Locality-Aware Attention with Transformers for General Geometry PDEs

Year: 2025 / Author: Minsu Koh, Beom-Chul Park, Heejo Kong, Seong-Whan Lee / Conference: International Joint Conference on Neural Networks (IJCNN)

#Breakthrough in Neural Scaling Law

ACoRN: Noise-Robust Abstractive Compression in Retrieval-Augmented Language Models

Year: 2025 / Author: Singon Kim, Gunho Jung, Seong-Whan Lee / Conference: International Joint Conference on Neural Networks (IJCNN)

#Breakthrough in Neural Scaling Law

Confidence-Weighted Boundary-Aware Learning for Semi-Supervised Semantic Segmentation

Year: 2025 / Author: Ebenezer Tarubinga, Jenifer Kalafatovich, Seong-Whan Lee / Conference: International Joint Conference on Neural Networks (IJCNN)

#Breakthrough in Neural Scaling Law

ProPose: Probabilistic 3D Human Pose Estimation with Instance-Level Distribution and Normalizing Flow

Year: 2025 / Author: Jumin Han, Jun-Hee Kim, Seong-Whan Lee / Conference: Association for the Advancement of Artificial Intelligence (AAAI)

#Breakthrough in Neural Scaling Law

FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning

Year: 2025 / Author: Woosung Kim, Jinho Lee, Jongmin Lee, Byung-Jun Lee / Conference: Advances in Neural Information Processing Systems (NeurIPS)

#Breakthrough in Neural Scaling Law

PLATYPUS: Progressive Local Surface Estimator for Arbitrary-Scale Point Cloud Upsampling

Year: 2025 / Author: Donghyun Kim, Hyeonkyeong Kwon, Yumin Kim, Seong Jae Hwang / Conference: The Association for the Advancement of Artificial Intelligence (AAAI)

#Breakthrough in Neural Scaling Law

Mono-Modalizing Extremely Heterogeneous Multi-Modal Medical Image Registration

Year: 2025 / Author: Kyobin Choo, Hyunkyung Han, Jinyeong Kim, Chanyong Yoon, Seong Jae Hwang / Conference: Medical Image Computing and Computer Assisted Intervention (MICCAI)

#Breakthrough in Neural Scaling Law

Pathology-Aware Adaptive Watermarking for Text-Driven Medical Image Synthesis

Year: 2025 / Author: Chanyoung Kim, Dayun Ju, Jinyeong Kim, Woojung Han, Roberto Alcover-Couso, Seong Jae Hwang / Conference: Medical Image Computing and Computer Assisted Intervention (MICCAI)

#Breakthrough in Neural Scaling Law

PRETI: Patient-Aware Retinal Foundation Model via Metadata-Guided Representation Learning

Year: 2025 / Author: Yeonkyung Lee, Woojung Han, Youngjun Jun, Hyeonmin Kim, Jungkyung Cho, Seong Jae Hwang / Conference: Medical Image Computing and Computer Assisted Intervention (MICCAI)

Publications