PaveVQA - Classification Accuracy: leaderboard
Metric: Classification accuracy (%) on categorical questions about distress presence and type, of the zero-shot model on PaveVQA, the vision-language question answering part of PaveBench (real highway pavement images, single-turn, multi-turn and expert-corrected questions); higher is better. Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 3 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Qwen2.5-VL-3B | 65.18 |
| 2 | LLaVA-OneVision-7B | 60.91 |
| 3 | DeepSeek-VL2-small | 55.48 |
Interactive version: theaggregate.ai/benchmark?slug=pavevqa-classification-accuracy · How It Works · Data refreshed daily, snapshot 2026-10-07.