MedXpertQA-MM

MedXpertQA-MM is a benchmark for understanding images combined with text. The official description says: "MedXpertQA-MM - multimodal medical expert question answering benchmark evaluating clinical reasoning with visual inputs". Below we describe in simple words what benchmarks of this type generally examine.

MedXpertQA-MM measures understanding images combined with text. In detail, it checks:

• answering questions about images (figures, photos, charts, memes)
• reading text inside images and connecting it to the question
• visual reasoning such as counting, locating and comparing objects
• combining what is seen with general knowledge

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Official methodology note: MedXpertQA-MM - multimodal medical expert question answering benchmark evaluating clinical reasoning with visual inputs.

What is the MedXpertQA-MM benchmark?

MedXpertQA-MM is a benchmark for understanding images combined with text. The official description says: 'MedXpertQA-MM - multimodal medical expert question answering benchmark evaluating clinical reasoning with visual inputs'. Below we describe in simple words what benchmarks of this type generally examine.

What does MedXpertQA-MM test?

MedXpertQA-MM mainly measures understanding images combined with text. Concretely, it checks: answering questions about images (figures, photos, charts, memes); reading text inside images and connecting it to the question; visual reasoning such as counting, locating and comparing objects.

How is the MedXpertQA-MM score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Where do I get MedXpertQA-MM data and scores?

The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/medxpertqa-mm/scores) or pull it directly from the Open LLM Radar API with any HTTP client.