Fetal-Gauge benchmark shows state-of-the-art vision-language models reach only 55% accuracy on fetal ultrasound tasks, well below clinical needs and highlighting the requirement for domain-adapted models.
Fetalclip: A visual- language foundation model for fetal ultrasound image analysis.arXiv preprint arXiv:2502.14807
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2representative citing papers
DARK distillation lets a 75M-parameter student model match or exceed a 427M-parameter teacher on fetal ultrasound benchmarks by transitioning from imitating to repelling non-target similarities.
citing papers explorer
-
FETAL-GAUGE: A Benchmark for Assessing Vision-Language Models in Fetal Ultrasound
Fetal-Gauge benchmark shows state-of-the-art vision-language models reach only 55% accuracy on fetal ultrasound tasks, well below clinical needs and highlighting the requirement for domain-adapted models.
-
DARK: Diagonal-Anchored Repulsive Knowledge Distillation for Vision-Language Models under Extreme Compression
DARK distillation lets a 75M-parameter student model match or exceed a 427M-parameter teacher on fetal ultrasound benchmarks by transitioning from imitating to repelling non-target similarities.