In many deep neural network (DNN) applications, the difficulty of gathering high-quality data in the industry field hinders the practical use of DNN. Thus, the concept of transfer learning has emerged, which leverages the pretrained knowledge of DNNs trained on large-scale datasets. Therefore, this paper suggests two-stage architectural fine-tuning, inspired by neural architecture search (NAS). One of main ideas is mutation, which reduces the search cost using given architectural information. Moreover, early-stopping is considered which cuts NAS costs by terminating the search process in advance. Experimental results verify our proposed method reduces 32.4% computational and 22.3% searching costs.
MATHENA: Mamba-based Architectural Tooth Hierarchical Estimator and Holistic Evaluation Network for Anatomy
OUTTA；Seoul National University（首尔国立大学）；Sangmyung University（祥明大学）；Gwangju Institute of Science and Technology（光州科学技术院）；Samsung Medical Center, Sungkyunkwan University（三星医学中心，成均馆大学）；Samsung Changwon Hospital, Sungkyunkwan University（三星昌原医院，成均馆大学）；NVIDIA AI Technology Center（英伟达人工智能技术中心）
Equivariant-Aware Structured Pruning for Efficient Edge Deployment: A Comprehensive Framework with Adaptive Fine-Tuning
Faculty of Computers and Information Technology, University of Tabuk（计算机与信息科技学院，塔布克大学）；Artificial Intelligence and Sensing Technologies (AIST) Research Center, University of Tabuk（人工智能与传感技术（AIST）研究中心，塔布克大学）
Self-Tuning Regularization for Image Scanning Microscopy
MaLGa Center, DIBRIS, University of Genoa（MaLGa中心，DIBRIS，热那亚大学）；MMS, Istituto Italiano di Tecnologia (IIT)（MMS，意大利技术研究院（IIT））；CSML, Istituto Italiano di Tecnologia (IIT)（CSML，意大利技术研究院（IIT））
Why Do MLLMs Struggle with Spatial Understanding? A Systematic Analysis from Data to Architecture
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；Tsinghua University（清华大学）；Harbin Institute of Technology（哈尔滨工业大学）；Wuhan AI Research（武汉人工智能研究院）；Institute of Microelectronics of the Chinese Academy of Sciences（中国科学院微电子研究所）
DS@GT ARC at ImageCLEFmedical 2026: Architectural Diversity for Concept Detection and Foundation-Model Scaling for Caption Prediction in Medical Image Analysis
