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Visual Question Answering

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Showing 1676–1700 of 2177 papers

TitleStatusHype
EVJVQA Challenge: Multilingual Visual Question Answering—0
VolDoGer: LLM-assisted Datasets for Domain Generalization in Vision-Language Tasks—0
VQA-Aid: Visual Question Answering for Post-Disaster Damage Assessment and Analysis—0
VQABQ: Visual Question Answering by Basic Questions—0
VQA-Diff: Exploiting VQA and Diffusion for Zero-Shot Image-to-3D Vehicle Asset Generation in Autonomous Driving—0
VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions—0
VQA-GEN: A Visual Question Answering Benchmark for Domain Generalization—0
VQA-GNN: Reasoning with Multimodal Knowledge via Graph Neural Networks for Visual Question Answering—0
VQA-LOL: Visual Question Answering under the Lens of Logic—0
VQA-MHUG: A Gaze Dataset to Study Multimodal Neural Attention in Visual Question Answering—0
VQA Training Sets are Self-play Environments for Generating Few-shot Pools—0
VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models—0
VQA with Cascade of Self- and Co-Attention Blocks—0
VSA4VQA: Scaling a Vector Symbolic Architecture to Visual Question Answering on Natural Images—0
WangLab at MEDIQA-M3G 2024: Multimodal Medical Answer Generation using Large Language Models—0
Weak Supervision helps Emergence of Word-Object Alignment and improves Vision-Language Tasks—0
What If We Recaption Billions of Web Images with LLaMA-3?—0
What is needed for simple spatial language capabilities in VQA?—0
What Large Language Models Bring to Text-rich VQA?—0
When are Lemons Purple? The Concept Association Bias of Vision-Language Models—0
Where is this coming from? Making groundedness count in the evaluation of Document VQA models—0
Where To Look: Focus Regions for Visual Question Answering—0
Which Client is Reliable?: A Reliable and Personalized Prompt-based Federated Learning for Medical Image Question Answering—0
Why context matters in VQA and Reasoning: Semantic interventions for VLM input modalities—0
Why Does a Visual Question Have Different Answers?—0
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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