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Visual Question Answering

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TitleStatusHype
Recurrent and Contextual Models for Visual Question Answering—0
Visual Question Answering for Cultural Heritage—0
CLIP-Powered TASS: Target-Aware Single-Stream Network for Audio-Visual Question Answering—0
WoLF: Wide-scope Large Language Model Framework for CXR Understanding—0
Reducing Hallucinations: Enhancing VQA for Flood Disaster Damage Assessment with Visual Contexts—0
Reducing Language Biases in Visual Question Answering with Visually-Grounded Question Encoder—0
CLIP Models are Few-shot Learners: Empirical Studies on VQA and Visual Entailment—0
Visual question answering: from early developments to recent advances -- a survey—0
Regularizing Attention Networks for Anomaly Detection in Visual Question Answering—0
Visual Question Answering in Ophthalmology: A Progressive and Practical Perspective—0
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All datasetsMM-VetViP-BenchVQA v2 test-devBenchLMMMMBenchV*benchVQA v2 valMSRVTT-QAVQA v2 test-stdMMHal-BenchMSVD-QAPlotQA-D1

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MMCTAgent (GPT-4 + GPT-4V)GPT-4 score74.24—Unverified
2Qwen2-VL-72BGPT-4 score74—Unverified
3InternVL2.5-78BGPT-4 score72.3—Unverified
4GPT-4o +text rationale +IoTGPT-4 score72.2—Unverified
5Lyra-ProGPT-4 score71.4—Unverified
6GLM-4V-PlusGPT-4 score71.1—Unverified
7Phantom-7BGPT-4 score70.8—Unverified
8InternVL2.5-38BGPT-4 score68.8—Unverified
9InternVL2-26B (SGP, token ratio 64%)GPT-4 score65.6—Unverified
10Baichuan-Omni (7B)GPT-4 score65.4—Unverified