8 papers
Kalman Filter Enhanced GRPO for Reinforcement Learning-Based Language Model Reasoning
Hu Wang, Congbo Ma, Ian Reid +1
The advantage function is a central concept in RL that helps reduce variance in policy gradient estimates. For language modeling, Group Relative Policy Optimization (GRPO) was prop…
T3: Test-Time Model Merging in VLMs for Zero-Shot Medical Imaging Analysis
Raza Imam, Hu Wang, Dwarikanath Mahapatra +1
In medical imaging, vision-language models face a critical duality: pretrained networks offer broad robustness but lack subtle, modality-specific characteristics, while fine-tuned…
EMedNeXt: An Enhanced Brain Tumor Segmentation Framework for Sub-Saharan Africa using MedNeXt V2 with Deep Supervision
Ahmed Jaheen, Abdelrahman Elsayed, Damir Kim +8
Brain cancer affects millions worldwide, and in nearly every clinical setting, doctors rely on magnetic resonance imaging (MRI) to diagnose and monitor gliomas. However, the curren…
DuPLUS: Dual-Prompt Vision-Language Framework for Universal Medical Image Segmentation and Prognosis
Numan Saeed, Tausifa Jan Saleem, Fadillah Maani +3
Deep learning for medical imaging is hampered by task-specific models that lack generalizability and prognostic capabilities, while existing 'universal' approaches suffer from simp…
Predicting Brain Tumor Response to Therapy using a Hybrid Deep Learning and Radiomics Approach
Daniil Tikhonov, Matheus Scatolin, Mohor Banerjee +7
Accurate evaluation of the response of glioblastoma to therapy is crucial for clinical decision-making and patient management. The Response Assessment in Neuro-Oncology (RANO) crit…
SALT: Parameter-Efficient Fine-Tuning via Singular Value Adaptation with Low-Rank Transformation
Abdelrahman Elsayed, Sarim Hashmi, Mohammed Elseiagy +3
The complex nature of medical image segmentation calls for models that are specifically designed to capture detailed, domain-specific features. Large foundation models offer consid…