Our new X account is live! Follow @wizwand_team for updates

Medical Visual Question Answering on VQA-RAD closed-end

84.86Accuracy

V2T-COT(Phi2)

Updated 3d ago

Evaluation Results

Method	Links
V2T-COT(Phi2) 2025.06		84.86
LLaVA-Med 2024.04		84.2
LLaVA-Med(LLama) 2025.06		84.19
MedThink 2025.06		83.5
VL Encoder-Decoder 2025.06		82.47
LLaVA-Med(Vicuna) 2025.06		81.98
LLaVA-Med(Phi2) 2025.06		81.35
Q2ATransformer 2025.06		81.2
V2T-COT(Phi2) 2025.06		80.1
V2T-COT (Stablelm) 2025.06		80.08
Med-MoE 2025.06		80.07
PubMedCLIP 2025.06		80
V2T-COT (Stablelm) 2025.06		79.69
MEDALIGN 2025.12		78.74
AVISC 2025.12		78.35
MMBERT 2025.06		78.1
VCD 2025.12		77.95
DoLa 2025.12		77.95
M3ID 2025.12		77.95
DAMRO 2025.12		77.95
MMBERT 2025.06		77.9
Nucleus 2025.12		77.56
PAI 2025.12		77.17
Greedy 2025.12		76.77
Beam 2025.12		76.77
OPERA 2025.12		76.77
Med-MoE 2025.06		76.56
OPERA 2025.12		74.8
MEDALIGN 2025.12		74.8
Greedy 2025.12		74.41
Beam 2025.12		74.41
DoLa 2025.12		74.41
AVISC 2025.12		74.41
PAI 2025.12		74.41
M3ID 2025.12		74.02
Nucleus 2025.12		73.62
VCD 2025.12		73.62
DAMRO 2025.12		73.62
LLaVA-1.5 2024.04		68.9
MOVA 2024.04		68.9
BiomedGPT-M 2025.06		65.07
LLAVA 2025.06		65.07
Gemini Pro 2025.06		60.29
Gemini Pro 2025.06		60.22
LLaVA-Med 2024.04		56.3