Image Classification on DermaMNIST
86.2AccuracyBiomedGPT
Evaluation Results
| Method | Links | |
|---|---|---|
| BiomedGPTCategory=Finetuned Medical MLLMs2026.03 | 86.2 | |
| Clinician Mimetic WorkflowCategory=Proposed2026.03 | 83.6 | |
| SigLIP2-BCategory=Supervised (Full-Tuning)2026.03 | 81.8 | |
| SaEBudget=20%, Number of seeds=52026.02 | 80.21 | |
| Swin-BCategory=Supervised (Full-Tuning)2026.03 | 79.5 | |
| Hulu-MedCategory=Finetuned Medical MLLMs2026.03 | 77.7 | |
| ViT-BCategory=Supervised (Full-Tuning)2026.03 | 76.6 | |
| L1 KDE-XEBackbone=ResNet-110 (SD)2022.10 | 76.4 | |
| TIESBackbone=ViT-L/16, Number of samples=5002026.06 | 76.4 | |
| ConvNeXt-BCategory=Supervised (Full-Tuning)2026.03 | 76.2 | |
| DARE-TIESBackbone=ViT-L/16, Number of samples=5002026.06 | 76.2 | |
| Domain onlyBackbone=ViT-L/16, Number of samples=5002026.06 | 76.1 | |
| TaDABackbone=ViT-L/16, Number of samples=5002026.06 | 76 | |
| MMCEBackbone=DenseNet-402022.10 | 75.8 | |
| SVD MergeBackbone=ViT-L/16, Number of samples=5002026.06 | 75.8 | |
| MedCoOp + BADGEBudget=20%, Number of seeds=52026.02 | 75.46 | |
| L1 KDE-XEBackbone=Wide-ResNet-28-102022.10 | 75.4 | |
| MMCEBackbone=ResNet-110 (SD)2022.10 | 75.3 | |
| LinearBackbone=ViT-L/16, Number of samples=5002026.06 | 75 | |
| L1 KDE-XEBackbone=DenseNet-402022.10 | 74.8 | |
| Task onlyBackbone=ViT-L/16, Number of samples=5002026.06 | 74.8 | |
| MedCoOp + EntropyBudget=20%, Number of seeds=52026.02 | 74.56 | |
| L1 KDE-XEBackbone=ResNet-1102022.10 | 74.4 | |
| XEBackbone=ResNet-110 (SD)2022.10 | 74.3 | |
| DARE-LinBackbone=ViT-L/16, Number of samples=5002026.06 | 74.2 | |
| Mag. PruningBackbone=ViT-L/16, Number of samples=5002026.06 | 74.2 | |
| MedCoOp + CoresetBudget=20%, Number of seeds=52026.02 | 74.11 | |
| MMCEBackbone=Wide-ResNet-28-102022.10 | 74.1 | |
| XEBackbone=DenseNet-402022.10 | 74.1 | |
| XEBackbone=Wide-ResNet-28-102022.10 | 73.6 | |
| ResNet50Category=Supervised (Full-Tuning)2026.03 | 73 | |
| Task Arith.Backbone=ViT-L/16, Number of samples=5002026.06 | 72.6 | |
| Base modelBackbone=ViT-L/16, Number of samples=5002026.06 | 72.2 | |
| MMCEBackbone=ResNet-1102022.10 | 72.1 | |
| XEBackbone=ResNet-1102022.10 | 72 | |
| FL-53Backbone=Wide-ResNet-28-102022.10 | 71.5 | |
| PCBBudget=20%, Number of seeds=52026.02 | 71.07 | |
| FL-53Backbone=DenseNet-402022.10 | 70.5 | |
| RandomBudget=20%, Number of seeds=52026.02 | 69.42 | |
| FL-53Backbone=ResNet-110 (SD)2022.10 | 68.9 | |
| FL-53Backbone=ResNet-1102022.10 | 67.4 | |
| BioMedVRSetting=Few-shot, Shots=16, Backbone=ViT-B/162026.06 | 65.3 | |
| VPSetting=Few-shot, Shots=16, Backbone=ViT-B/162026.06 | 64.9 | |
| BiomedCoOpBudget=20%, Number of seeds=5, inference_mode=few-shot reference2026.02 | 62.59 | |
| Gemini-3-flashCategory=General MLLMs2026.03 | 62.1 | |
| AttrVRSetting=Few-shot, Shots=16, Backbone=ViT-B/162026.06 | 61.6 | |
| BioMedCoOpSetting=Few-shot, Shots=16, Backbone=ViT-B/162026.06 | 59.9 | |
| ARSetting=Few-shot, Shots=16, Backbone=ViT-B/162026.06 | 58 | |
| BiomedCLIPPrediction Mode=Zero-shot2026.03 | 45.89 | |
| CoCoOpSetting=Few-shot, Shots=16, Backbone=ViT-B/162026.06 | 44 | |
| CoOpSetting=Few-shot, Shots=16, Backbone=ViT-B/162026.06 | 43 | |
| GPT-5-miniCategory=General MLLMs2026.03 | 37.4 | |
| MedGemmaCategory=Medical MLLMs2026.03 | 32.8 | |
| CLIPPrediction Mode=Zero-shot2026.03 | 24.74 | |
| BioMedCLIPSetting=Zero-shot, Shots=0, Backbone=ViT-B/162026.06 | 19.3 | |
| BioMedVRSetting=Zero-shot, Shots=0, Backbone=ViT-B/162026.06 | 13.9 | |
| CLIPSetting=Zero-shot, Shots=0, Backbone=ViT-B/162026.06 | 13 | |
| LLaVA-MedCategory=Medical MLLMs2026.03 | 12.9 | |
| SigLIP2Prediction Mode=Zero-shot2026.03 | 11.67 | |
| AttrVRSetting=Zero-shot, Shots=0, Backbone=ViT-B/162026.06 | 9.7 | |
| SigLIPPrediction Mode=Zero-shot2026.03 | 8.28 | |
| BioMedVRSetting=Zero-shot, Shots=0, Backbone=ViT-B/16, Pre-trained Model=BioMedCLIP2026.06 | 4.8 |