69 citations · 146 across the 27 of their papers we have counts for
5 papers · 1 filter
Case2Flow: Bridging Patient Cases and Guideline Flowcharts through Multimodal Retrieval
Jiale Wei, Yufan Chen, Alexander Jaus +5
Medical guidelines encode rich, evidence-based decision logic, yet the specific decision artifact a clinician needs is hard to locate within a guideline, let alone across guideline…
Quo Vadis, Visual In-Context Learning? A Unified Benchmark Across Domains and Tasks
Pradnya Halady, Jiale Wei, Zdravko Marinov +2
Visual in-context learning has been proposed as a pathway towards dynamic models that can generate predictions based on a provided context and thereby can adapt to new vision tasks…
Beyond Model Size: Probing the Gaps in Visual in-Context Learning by Training a Tiny Model
Sunil Khatri, Steven Landgraf, Markus Ulrich +1
Visual in-Context Learning (VICL) aims at making progress towards adaptive vision models, that can -- based on a few examples -- adapt to a new task at test-time. With the history…
From Static to Interactive: Adapting Visual in-Context Learners for User-Driven Tasks
Carlos Schmidt, Simon Reiß
Visual in-context learning models are designed to adapt to new tasks by leveraging a set of example input-output pairs, enabling rapid generalization without task-specific fine-tun…
Probing Intrinsic Medical Task Relationships: A Contrastive Learning Perspective
Jonas Muth, Zdravko Marinov, Simon Reiß
While much of the medical computer vision community has focused on advancing performance for specific tasks, the underlying relationships between tasks, i.e., how they relate, over…