5 papers
FrugalPrompt: Reducing Contextual Overhead in Large Language Models via Token Attribution
Syed Rifat Raiyan, Md Farhan Ishmam, Abdullah Al Imran +1
Human communication heavily relies on laconism and inferential pragmatics, allowing listeners to successfully reconstruct rich meaning from sparse, telegraphic speech. In contrast,…
Autoadaptive Medical Segment Anything Model
Tyler Ward, Meredith K. Owen, O'Kira Coleman +2
Medical image segmentation is a key task in the imaging workflow, influencing many image-based decisions. Traditional, fully-supervised segmentation models rely on large amounts of…
Differential Attention for Multimodal Crisis Event Analysis
Nusrat Munia, Junfeng Zhu, Olfa Nasraoui +1
Social networks can be a valuable source of information during crisis events. In particular, users can post a stream of multimodal data that can be critical for real-time humanitar…
Scout-Dose-TCM: Direct and Prospective Scout-Based Estimation of Personalized Organ Doses from Tube Current Modulated CT Exams
Maria Jose Medrano, Sen Wang, Liyan Sun +5
This study proposes Scout-Dose-TCM for direct, prospective estimation of organ-level doses under tube current modulation (TCM) and compares its performance to two established metho…
Annotation-Efficient Task Guidance for Medical Segment Anything
Tyler Ward, Abdullah-Al-Zubaer Imran
Medical image segmentation is a key task in the imaging workflow, influencing many image-based decisions. Traditional, fully-supervised segmentation models rely on large amounts of…