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Multi-modal Evaluation on MME-RW

31.9Mean AccuracyTTAug
25.97227.51129.0530.589Oct 3, 2025

Evaluation results

MethodLinks
TTAugAdaptation strategy=Test-time Augmentation2025.1031.9———
(2)Adaptation strategy=Model parameter adaptation2025.1031.4———
TTAugtest-time scaling=Method 52025.1031.1———
(1)Adaptation strategy=(1)2025.1030.9———
Baselinetest-time scaling=none2025.1027.8———
Baseline2025.1027.8———
Method ③test-time scaling=Other method 32025.1027.6———
Method ④test-time scaling=Other method 42025.1027.6———
Method ②test-time scaling=Other method 22025.1026.4———
Method ①test-time scaling=Other method 12025.1026.2———
Adaptive-CoFReasoning Paradigm=Thinking with Images, Base Model=Qwen2.5-VL-7B2026.02—50.9——
DeepEyesReasoning Paradigm=Thinking with Images, Base Model=Qwen2.5-VL-7B2026.02—49.5——
GPT-4oModel=GPT-4o2025.09—45.246.442.3
HiDeModel=Qwen2.5-VL 7B2025.09—63.866.742.9
MIRRORReasoning Paradigm=Thinking with Images, Base Model=Qwen2.5-VL-7B2026.02—51.49——
PixelReasonerReasoning Paradigm=Thinking with Images, Base Model=Qwen2.5-VL-7B2026.02—49.7——
Qwen2.5-VL 7BModel=Qwen2.5-VL 7B2025.09—61.464.340.1
VicropModel=Qwen2.5-VL 7B2025.09—62.365.142
VL-RethinkerReasoning Paradigm=Text Reflection, Base Model=Qwen2.5-VL-7B2026.02—47.21——