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 601–650 of 2167 papers

TitleStatusHype
How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering?—0
Can Common VLMs Rival Medical VLMs? Evaluation and Strategic Insights—0
MEGC2025: Micro-Expression Grand Challenge on Spot Then Recognize and Visual Question Answering—0
Adapting Lightweight Vision Language Models for Radiological Visual Question AnsweringCode0
ASCD: Attention-Steerable Contrastive Decoding for Reducing Hallucination in MLLM—0
Connecting phases of matter to the flatness of the loss landscape in analog variational quantum algorithms—0
CAPO: Reinforcing Consistent Reasoning in Medical Decision-Making—0
EyeSim-VQA: A Free-Energy-Guided Eye Simulation Framework for Video Quality Assessment—0
SlotPi: Physics-informed Object-centric Reasoning ModelsCode0
Scientists' First Exam: Probing Cognitive Abilities of MLLM via Perception, Understanding, and Reasoning—0
HalLoc: Token-level Localization of Hallucinations for Vision Language ModelsCode0
Outside Knowledge Conversational Video (OKCV) Dataset -- Dialoguing over VideosCode0
Kvasir-VQA-x1: A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal EndoscopyCode0
Provoking Multi-modal Few-Shot LVLM via Exploration-Exploitation In-Context Learning—0
PhyBlock: A Progressive Benchmark for Physical Understanding and Planning via 3D Block Assembly—0
From Pixels to Graphs: using Scene and Knowledge Graphs for HD-EPIC VQA Challenge—0
Looking Beyond Visible Cues: Implicit Video Question Answering via Dual-Clue ReasoningCode0
HAIBU-ReMUD: Reasoning Multimodal Ultrasound Dataset and Model Bridging to General Specific DomainsCode0
Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning—0
Ontology-based knowledge representation for bone disease diagnosis: a foundation for safe and sustainable medical artificial intelligence systems—0
ReXVQA: A Large-scale Visual Question Answering Benchmark for Generalist Chest X-ray Understanding—0
CoRe-MMRAG: Cross-Source Knowledge Reconciliation for Multimodal RAG—0
Fast or Slow? Integrating Fast Intuition and Deliberate Thinking for Enhancing Visual Question Answering—0
MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning—0
Vision LLMs Are Bad at Hierarchical Visual Understanding, and LLMs Are the Bottleneck—0
Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting—0
Multi-Sourced Compositional Generalization in Visual Question AnsweringCode0
A Comprehensive Evaluation of Multi-Modal Large Language Models for Endoscopy Analysis—0
Spoken question answering for visual queries—0
Synthetic Document Question Answering in HungarianCode0
MMSI-Bench: A Benchmark for Multi-Image Spatial Intelligence—0
NegVQA: Can Vision Language Models Understand Negation?—0
VIGNETTE: Socially Grounded Bias Evaluation for Vision-Language ModelsCode0
FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question AnsweringCode0
Silence is Not Consensus: Disrupting Agreement Bias in Multi-Agent LLMs via Catfish Agent for Clinical Decision Making—0
Diagnosing and Mitigating Modality Interference in Multimodal Large Language ModelsCode0
Benchmarking Large Multimodal Models for Ophthalmic Visual Question Answering with OphthalWeChat—0
MMIG-Bench: Towards Comprehensive and Explainable Evaluation of Multi-Modal Image Generation Models—0
TDVE-Assessor: Benchmarking and Evaluating the Quality of Text-Driven Video Editing with LMMs—0
Medical Large Vision Language Models with Multi-Image Visual AbilityCode0
GC-KBVQA: A New Four-Stage Framework for Enhancing Knowledge Based Visual Question Answering Performance—0
NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and ResultsCode0
Improving Medical Reasoning with Curriculum-Aware Reinforcement Learning—0
Focus on What Matters: Enhancing Medical Vision-Language Models with Automatic Attention Alignment Tuning—0
CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answering—0
A Causal Approach to Mitigate Modality Preference Bias in Medical Visual Question Answering—0
Grounding Chest X-Ray Visual Question Answering with Generated Radiology Reports—0
Steering LVLMs via Sparse Autoencoder for Hallucination Mitigation—0
MedFrameQA: A Multi-Image Medical VQA Benchmark for Clinical Reasoning—0
Zero-Shot Anomaly Detection in Battery Thermal Images Using Visual Question Answering with Prior Knowledge—0
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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