VlmsAreBlind

VlmsAreBlind is a benchmark for understanding images combined with text. The official description says: "VlmsAreBlind - benchmark testing visual perception capabilities that reveal blind spots in VLMs". Below we describe in simple words what benchmarks of this type generally examine.

VlmsAreBlind 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: VlmsAreBlind - benchmark testing visual perception capabilities that reveal blind spots in VLMs.

What is the VlmsAreBlind benchmark?

VlmsAreBlind is a benchmark for understanding images combined with text. The official description says: 'VlmsAreBlind - benchmark testing visual perception capabilities that reveal blind spots in VLMs'. Below we describe in simple words what benchmarks of this type generally examine.

What does VlmsAreBlind test?

VlmsAreBlind 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 VlmsAreBlind score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.

Where do I get VlmsAreBlind 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/vlmsareblind/scores) or pull it directly from the Open LLM Radar API with any HTTP client.