10 papers
Model Merging as Probabilistic Inference in Fine-Tuning Parameter Space
Long Minh Bui, Tuan Anh Le Van, Tung Phi Duc +3
Model merging aims to combine existing single-task solutions into a multi-task solution without additional data-driven fine-tuning.~Most existing approaches achieve this using geom…
SelectAnyTree: A Promptable Instance Segmentation Model for 3D Forest LiDAR Point Clouds
Trung Thanh Nguyen, Daniel Lusk, Kilian Gerberding +10
Automated instance segmentation of forest LiDAR point clouds is increasingly critical as forest monitoring moves toward scalable, detailed, 3D measurement. Yet, progress is constra…
Cross-Modal Knowledge Distillation without Paired Data: Theoretical Foundation and Algorithm
Trong Khiem Tran, Anh Duc Chu, Quang Hung Pham +2
Cross-modal knowledge distillation (CMKD) studies how a (large) teacher model trained on one type of data (e.g., images) can guide a (smaller) student model building on another typ…
Region-Grounded Report Generation for 3D Medical Imaging: A Fine-Grained Dataset and Graph-Enhanced Framework
Cong Huy Nguyen, Son Dinh Nguyen, Guanlin Li +8
Automated medical report generation for 3D PET/CT imaging is fundamentally challenged by the high-dimensional nature of volumetric data and a critical scarcity of annotated dataset…
Diffusion-Inspired Reconfiguration of Transformers for Uncertainty Calibration
Manh Cuong Dao, Quang Hung Pham, Phi Le Nguyen +3
Uncertainty calibration in pre-trained transformers is critical for their reliable deployment in risk-sensitive applications. Yet, most existing pre-trained transformers do not hav…
Rethinking Cross-Modal Fine-Tuning: Optimizing the Interaction Between Feature Alignment and Target Fitting
Trong Khiem Tran, Manh Cuong Dao, Phi Le Nguyen +2
Adapting pre-trained models to unseen feature modalities has become increasingly important due to the growing need for cross-disciplinary knowledge integration. A key challenge her…