ELSS - Landing Site Filtering (Nanjing): leaderboard
ELSS (Hua et al., 2026) tests multimodal models as the visual safety filter of a UAV emergency-landing pipeline: shown a remote-sensing image patch of a candidate landing site, the model answers Safe or Unsafe. F1 in percent (higher is better) against human suitability labels for 100 candidate sites proposed by semantic segmentation on 0.3 m satellite imagery of Nanjing.
Metric: F1 (%; the model judges each candidate landing site in a remote-sensing image patch Safe or Unsafe, scored against human suitability labels of 100 semantic-segmentation recommendations; Nanjing satellite imagery, 63 suitable sites). Source: arxiv.org. Saturation forecast: Not forecast. 5 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Grok 4.20 | 83.2 | #296 |
| 2 | GPT-5.4 | 82.5 | #121 |
| 3 | Seed 2.0 Pro | 77.2 | #209 |
| 4 | Gemini 3.1 Pro (Preview) | 72.9 | #91 |
| 5 | Claude Opus 4.6 | 72.1 | #100 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=elss-landing-site-filtering-nanjing · How It Works · Data refreshed daily, snapshot 2026-11-12.