4 papers
Multimodal Model Diffing for Feature Discovery and Control
Hunar Batra, Lachin Naghashyar, Ashkan Khakzar +4
Multimodal Large Language Models (MLLMs) exhibit strong visual understanding, yet the internal features that cause these behaviors remain difficult to identify, audit, or control.…
Towards Understanding Multimodal Fine-Tuning: Spatial Features
Lachin Naghashyar, Hunar Batra, Ashkan Khakzar +4
Contemporary Vision-Language Models (VLMs) achieve strong performance on a wide range of tasks by pairing a vision encoder with a pre-trained language model, fine-tuned for visual-…
Improving Myocardial Infarction Detection via Synthetic ECG Pretraining
Lachin Naghashyar
Myocardial infarction is a major cause of death globally, and accurate early diagnosis from electrocardiograms (ECGs) remains a clinical priority. Deep learning models have shown p…
Enhanced Synthetic MRI Generation from CT Scans Using CycleGAN with Feature Extraction
Saba Nikbakhsh, Lachin Naghashyar, Morteza Valizadeh +1
In the field of radiotherapy, accurate imaging and image registration are of utmost importance for precise treatment planning. Magnetic Resonance Imaging (MRI) offers detailed imag…