MC-CXR - Misleading Overlay: leaderboard

Accuracy on MC-CXR (Seoul National University, 2026) over the 199 off-finding overlay cases: the chest X-ray comes with a PACS-style arrow drawn away from the pathology, and the model must name the image finding among 12 CheXpert labels. Raw target-finding accuracy in percent; higher is better.

Metric: Accuracy under misleading context (%; the image plus a PACS-style arrow pointing off the pathology; 240 radiologist-reviewed MIMIC-CXR cases, one current chest X-ray and a fixed target finding each; zero-shot constrained single-letter answer from 12 CheXpert labels (chance about 8.3%), invalid answers scored wrong; greedy or temperature-0 decoding). Source: arxiv.org. Saturation forecast: Around 2037. 10 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3.5 9B23.6#803
2MedGemma 1.5 4B19.6#2562
3Gemini 3.5 Flash (Minimal)11.6#101 (Gemini 3.5 Flash)
4Llama 3.2 11B Instruct11.1#4991
5InternVL3-8B10.6#1688
6Claude Opus 4.710.6#79
7Phi-4 Multimodal Instruct7.5#3882
8Gemma 3 12B (IT)6#1837

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=mc-cxr-misleading-overlay · How It Works · Data refreshed daily, snapshot 2026-11-13.