SlakeVQA
A semantically-labeled knowledge-enhanced dataset for medical visual question answering. Contains 642 radiology images (CT scans, MRI scans, X-rays) covering five body parts and 14,028 bilingual English-Chinese question-answer pairs annotated by experienced physicians. Features comprehensive semantic labels and a structural medical knowledge base with both vision-only and knowledge-based questions requiring external medical knowledge reasoning.
4rows
scoreprimary metric
2026-05-06sampled
Metadata
Metrics
Score, Normalized Score
| Rank | Subject | Score | Model Match | Provenance | Sampled |
|---|---|---|---|---|---|
| 1 | Qwen3.5-122B-A10B | 0.82 |  Qwen3.5-122B-A10B qwen-qwen3.5-122b-a10b | Self-reported | 2026-05-06 |
| 2 | Qwen3.5-27B | 0.80 | Qwen3.5-27B qwen-qwen3.5-27b | Self-reported | 2026-05-06 |
| 3 | Qwen3.5-35B-A3B | 0.79 | Qwen3.5-35B-A3B qwen-qwen3.5-35b-a3b | Self-reported | 2026-05-06 |
| 4 | MedGemma 4B IT | 0.62 | — | Self-reported | 2026-05-06 |
No matching rows.