medical vision-language models

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papersTODAY 04:00 UTC

Paper measures and mitigates template collapse in 3D CT report generation

A new arXiv paper examines how 3D medical vision-language models can write fluent radiology-style reports while still missing critical findings and producing highly repetitive output. The authors characterize this behavior, which they call template collapse, noting that models default to generic phrasing that under-reports rare pathologies. They then propose ways to measure the problem and reduce it.

medical-imaging/vision-language-models/evaluation/safety

papersTODAY 04:00 UTC

EasyLens Boosts Subtle Lesion Detection in Medical Vision-Language Models

Researchers present EasyLens, a plug-and-play method that amplifies the representation of subtle lesions in medical vision-language models without requiring any additional training. The approach targets a known weakness of such models, whose clinical usefulness is limited by low sensitivity to faint or small abnormalities. According to the paper, the technique can be added to existing pipelines to improve lesion detection and related report generation tasks.

medical-imaging/vision-language/training-free/arxiv