| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| ScienceQA (test) | LLaVa + GPT-4 (judge) | Accuracy92.53 | 73 | 1mo ago | |
| MMBench CN | Qwen3-VL-8B | Accuracy84.6 | 61 | 22d ago | |
| ScienceQA | CASHEW | Accuracy97.8 | 61 | 1mo ago | |
| MMQA | Accuracy70.5 | 36 | 4mo ago | ||
| MMBench English | MMBen85.7 | 33 | 29d ago | ||
| WebQA Average | Nemo-Emb-1B | F1 Score50.8 | 32 | 1mo ago | |
| MMBench EN | Qwen3-VL-8B | Accuracy86.3 | 30 | 22d ago | |
| M2RAG | Ours-top3 | B-1 Score42.95 | 28 | 2mo ago | |
| SUPERGLASSES 1.0 (Leaderboard) | SUPERLENS‡ (Ours) | Accuracy (Easy)49.68 | 28 | 3mo ago | |
| ManyModalQA (test) | MAMMQA | Accuracy (Text)92.5 | 27 | 3mo ago | |
| MMBench en (test) | Accuracy89 | 26 | 3mo ago | ||
| LiveVQA | OpenSearch-VL-32B | Pass@170.5 | 24 | 2mo ago | |
| MM-Vet | Qwen3-VL-4B | Total Score68.3 | 24 | 4mo ago | |
| Aggregate (Open-WikiTable, 2WikiMQA, InfoSeek, Dyn-VQA, TabFact, WebQA) | MoRE-7B | Average Score55.93 | 22 | 3mo ago | |
| WebQA | MoRE-7B | F1-Recall90.92 | 22 | 3mo ago | |
| TabFact | MoRE-3B | F1-Recall52.6 | 22 | 3mo ago | |
| Dyn-VQA | R1-Distill-Qwen-32B | F1-Recall39.98 | 22 | 3mo ago | |
| 2WikiMQA | MoRE-7B | F1-Recall55.47 | 22 | 3mo ago | |
| Open-WikiTable | MoRE-7B | F1 Recall53.9 | 22 | 3mo ago | |
| ScienceQA v1.3 (test) | NAT Score0.9019 | 21 | 4mo ago | ||
| SEED-Bench | QMoSLoRA | Accuracy (All)71.1 | 21 | 4mo ago | |
| MMBench Chinese | MMBCN Score85.1 | 20 | 29d ago | ||
| MMQA | FES-RAG-top5 | BLEU-149.31 | 20 | 2mo ago | |
| MMQA k=1 | ROrig@k57.4 | 20 | 1mo ago | ||
| MME-RealWorld-Lite 1.0 (test) | HART-7B | Perception (AD) Acc57.7 | 19 | 4mo ago |
