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Visual Question Answering

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TitleStatusHype
Learning to Compress Contexts for Efficient Knowledge-based Visual Question Answering—0
Fine-tuning vs From Scratch: Do Vision & Language Models Have Similar Capabilities on Out-of-Distribution Visual Question Answering?—0
An experimental study of the vision-bottleneck in VQA—0
Learning to Disambiguate by Asking Discriminative Questions—0
Correlation Information Bottleneck: Towards Adapting Pretrained Multimodal Models for Robust Visual Question Answering—0
VDocRAG: Retrieval-Augmented Generation over Visually-Rich Documents—0
V-Doc : Visual questions answers with Documents—0
V-Doc: Visual Questions Answers With Documents—0
An Evaluation of GPT-4V and Gemini in Online VQA—0
Neural Reasoning, Fast and Slow, for Video Question Answering—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