SOTAVerified

Visual Question Answering (VQA)

Visual Question Answering (VQA) is a task in computer vision that involves answering questions about an image. The goal of VQA is to teach machines to understand the content of an image and answer questions about it in natural language.

Image Source: visualqa.org

Papers

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Showing 151–200 of 2167 papers

TitleStatusHype
Interpreting Chest X-rays Like a Radiologist: A Benchmark with Clinical ReasoningCode1
GeoLLaVA-8K: Scaling Remote-Sensing Multimodal Large Language Models to 8K ResolutionCode1
MineAnyBuild: Benchmarking Spatial Planning for Open-world AI AgentsCode1
Unifying Multimodal Large Language Model Capabilities and Modalities via Model MergingCode1
SATORI-R1: Incentivizing Multimodal Reasoning with Spatial Grounding and Verifiable RewardsCode1
Are Vision Language Models Ready for Clinical Diagnosis? A 3D Medical Benchmark for Tumor-centric Visual Question AnsweringCode1
Let Androids Dream of Electric Sheep: A Human-like Image Implication Understanding and Reasoning FrameworkCode1
MedAgentBoard: Benchmarking Multi-Agent Collaboration with Conventional Methods for Diverse Medical TasksCode1
MM-Skin: Enhancing Dermatology Vision-Language Model with an Image-Text Dataset Derived from TextbooksCode1
VideoMultiAgents: A Multi-Agent Framework for Video Question AnsweringCode1
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and ResultsCode1
Mimic In-Context Learning for Multimodal TasksCode1
STING-BEE: Towards Vision-Language Model for Real-World X-ray Baggage Security InspectionCode1
FaceBench: A Multi-View Multi-Level Facial Attribute VQA Dataset for Benchmarking Face Perception MLLMsCode1
AMD-Hummingbird: Towards an Efficient Text-to-Video ModelCode1
NuPlanQA: A Large-Scale Dataset and Benchmark for Multi-View Driving Scene Understanding in Multi-Modal Large Language ModelsCode1
MicroVQA: A Multimodal Reasoning Benchmark for Microscopy-Based Scientific ResearchCode1
Open3DVQA: A Benchmark for Comprehensive Spatial Reasoning with Multimodal Large Language Model in Open SpaceCode1
KVQ: Boosting Video Quality Assessment via Saliency-guided Local PerceptionCode1
MMUnlearner: Reformulating Multimodal Machine Unlearning in the Era of Multimodal Large Language ModelsCode1
Content-Rich AIGC Video Quality Assessment via Intricate Text Alignment and Motion-Aware ConsistencyCode1
Robust-LLaVA: On the Effectiveness of Large-Scale Robust Image Encoders for Multi-modal Large Language ModelsCode1
Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model EvaluationCode1
Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs?Code1
Notes-guided MLLM Reasoning: Enhancing MLLM with Knowledge and Visual Notes for Visual Question AnsweringCode1
MedCoT: Medical Chain of Thought via Hierarchical ExpertCode1
Fast Prompt Alignment for Text-to-Image GenerationCode1
IMPACT: A Large-scale Integrated Multimodal Patent Analysis and Creation Dataset for Design PatentsCode1
MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at ScaleCode1
AIGV-Assessor: Benchmarking and Evaluating the Perceptual Quality of Text-to-Video Generation with LMMCode1
Teaching VLMs to Localize Specific Objects from In-context ExamplesCode1
Awaker2.5-VL: Stably Scaling MLLMs with Parameter-Efficient Mixture of ExpertsCode1
An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal ModelsCode1
Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity DatasetCode1
Progressive Compositionality In Text-to-Image Generative ModelsCode1
WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global CuisinesCode1
VividMed: Vision Language Model with Versatile Visual Grounding for MedicineCode1
LiveXiv -- A Multi-Modal Live Benchmark Based on Arxiv Papers ContentCode1
Towards Foundation Models for 3D Vision: How Close Are We?Code1
Skipping Computations in Multimodal LLMsCode1
DataEnvGym: Data Generation Agents in Teacher Environments with Student FeedbackCode1
ActiView: Evaluating Active Perception Ability for Multimodal Large Language ModelsCode1
MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM IntegrationCode1
BadCM: Invisible Backdoor Attack Against Cross-Modal LearningCode1
A Hitchhikers Guide to Fine-Grained Face Forgery Detection Using Common Sense ReasoningCode1
T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness RecognitionCode1
MediConfusion: Can you trust your AI radiologist? Probing the reliability of multimodal medical foundation modelsCode1
Evaluating Image Hallucination in Text-to-Image Generation with Question-AnsweringCode1
Less is More: A Simple yet Effective Token Reduction Method for Efficient Multi-modal LLMsCode1
AIM 2024 Challenge on Compressed Video Quality Assessment: Methods and ResultsCode1
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All datasetsGQA Test2019VQA v2 test-devVQA v2 test-stdOK-VQAMSVD-QADocVQA testMSRVTT-QAInfographicVQAGQA test-devVizWiz 2020 VQAA-OKVQACLEVR

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1humanAccuracy89.3—Unverified
2DREAM+Unicoder-VL (MSRA)Accuracy76.04—Unverified
3TRRNet (Ensemble)Accuracy74.03—Unverified
4MIL-nbgaoAccuracy73.81—Unverified
5Kakao BrainAccuracy73.33—Unverified
6Coarse-to-Fine Reasoning, Single ModelAccuracy72.14—Unverified
7270Accuracy70.23—Unverified
8NSM ensemble (updated)Accuracy67.55—Unverified
9VinVL-DPTAccuracy64.92—Unverified
10VinVL+LAccuracy64.85—Unverified
#ModelMetricClaimedVerifiedStatus
1PaLIAccuracy84.3—Unverified
2BEiT-3Accuracy84.19—Unverified
3VLMoAccuracy82.78—Unverified
4ONE-PEACEAccuracy82.6—Unverified
5mPLUG (Huge)Accuracy82.43—Unverified
6CuMo-7BAccuracy82.2—Unverified
7X2-VLM (large)Accuracy81.9—Unverified
8MMUAccuracy81.26—Unverified
9InternVL-CAccuracy81.2—Unverified
10LyricsAccuracy81.2—Unverified
#ModelMetricClaimedVerifiedStatus
1BEiT-3overall84.03—Unverified
2mPLUG-Hugeoverall83.62—Unverified
3ONE-PEACEoverall82.52—Unverified
4X2-VLM (large)overall81.8—Unverified
5VLMooverall81.3—Unverified
6SimVLMoverall80.34—Unverified
7X2-VLM (base)overall80.2—Unverified
8VASToverall80.19—Unverified
9VALORoverall78.62—Unverified
10Prompt Tuningoverall78.53—Unverified