Reliability Stress Tests and Decision-Time Routing for Chest X-ray Vision-Language Models
Medical vision-language model (VLM) evaluation is sensitive to workflow design, prompting strategy, and benchmark construction, yet most studies treat these factors in isolation. We introduce a reliability stress test for chest X-ray interpretation built on two balanced datasets (a private report-backed set and a curated MIMIC subset). Three medical VLMs (CheXagent, MedGemma-4B, and MedGemma-27B) are evaluated across three prompt styles and two workflows (single-VLM and multi-agent), producing 36 configurations. We show that exact-match accuracy alone can overstate the effectiveness of conservative models that default to "Normal" predictions. Diagnostic reliability also depends heavily on...
| Authors | Xinye Yang, Zhusi Zhong, Scott Collins et al. |
|---|---|
| Primary category | eess.IV |
| Published | 1 October 2026 |
| Last updated at source | 1 October 2026 |
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