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Elke A. Rundensteiner

2 accepted papers

2026

PromptMoE: A Segmentation Refinement Framework Leveraging Mixture of Experts for Improved Prompting

CVPR 2026

High-quality segmentations are critical in vision tasks where boundary accuracy is important (e.g., medical diagnostics, quality control, etc.). Recently, promptable vision models have emerged as effective backbones for segmentation refinement frameworks. However, their performance not only hinges o

Cited by 0SourceScholar
2021

Semi-Supervised Knowledge Amalgamation for Sequence Classification

AAAI 2021technical

Sequence classification is essential for domains from medical diagnosis to online advertising. In these settings, data are typically proprietary, and annotations are expensive to acquire. Often times, so few annotations are available that training a robust model from scratch is impractical. Recently…