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Visual Question Answering

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Papers

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Showing 401–450 of 2177 papers

TitleStatusHype
Aligned Vector Quantization for Edge-Cloud Collabrative Vision-Language Models—0
Seeing is Deceiving: Exploitation of Visual Pathways in Multi-Modal Language Models—0
SaSR-Net: Source-Aware Semantic Representation Network for Enhancing Audio-Visual Question Answering—0
M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding—0
NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA—0
VQA^2: Visual Question Answering for Video Quality AssessmentCode2
Select2Plan: Training-Free ICL-Based Planning through VQA and Memory Retrieval—0
From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing—0
Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning AgentCode3
MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning—0
Multimodal Commonsense Knowledge Distillation for Visual Question Answering—0
One VLM to Keep it Learning: Generation and Balancing for Data-free Continual Visual Question Answering—0
Goal-Oriented Semantic Communication for Wireless Visual Question Answering—0
A Visual Question Answering Method for SAR Ship: Breaking the Requirement for Multimodal Dataset Construction and Model Fine-Tuning—0
RS-MoE: Mixture of Experts for Remote Sensing Image Captioning and Visual Question Answering—0
Designing a Robust Radiology Report Generation System—0
Right this way: Can VLMs Guide Us to See More to Answer Questions?Code0
Show Me What and Where has Changed? Question Answering and Grounding for Remote Sensing Change DetectionCode1
Nearest Neighbor Normalization Improves Multimodal RetrievalCode1
SimpsonsVQA: Enhancing Inquiry-Based Learning with a Tailored Dataset—0
GRADE: Quantifying Sample Diversity in Text-to-Image Models—0
Are VLMs Really BlindCode0
Few-Shot Multimodal Explanation for Visual Question AnsweringCode0
Attention Overlap Is Responsible for The Entity Missing Problem in Text-to-image Diffusion Models!—0
Face-MLLM: A Large Face Perception Model—0
Efficient Bilinear Attention-based Fusion for Medical Visual Question Answering—0
AutoBench-V: Can Large Vision-Language Models Benchmark Themselves?Code0
R-LLaVA: Improving Med-VQA Understanding through Visual Region of Interest—0
Sensor2Text: Enabling Natural Language Interactions for Daily Activity Tracking Using Wearable Sensors—0
GiVE: Guiding Visual Encoder to Perceive Overlooked Information—0
Visual Text Matters: Improving Text-KVQA with Visual Text Entity Knowledge-aware Large Multimodal AssistantCode0
Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks—0
Which Client is Reliable?: A Reliable and Personalized Prompt-based Federated Learning for Medical Image Question Answering—0
ADEM-VL: Adaptive and Embedded Fusion for Efficient Vision-Language TuningCode1
Progressive Compositionality In Text-to-Image Generative ModelsCode1
Order Matters: Exploring Order Sensitivity in Multimodal Large Language Models—0
Visual Question Answering in Ophthalmology: A Progressive and Practical Perspective—0
Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases—0
Griffon-G: Bridging Vision-Language and Vision-Centric Tasks via Large Multimodal Models—0
CROPE: Evaluating In-Context Adaptation of Vision and Language Models to Culture-Specific ConceptsCode0
ChitroJera: A Regionally Relevant Visual Question Answering Dataset for Bangla—0
LLaVA-Ultra: Large Chinese Language and Vision Assistant for Ultrasound—0
E3D-GPT: Enhanced 3D Visual Foundation for Medical Vision-Language Model—0
Zero-shot Action Localization via the Confidence of Large Vision-Language Models—0
NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples—0
ViConsFormer: Constituting Meaningful Phrases of Scene Texts using Transformer-based Method in Vietnamese Text-based Visual Question AnsweringCode0
MultiChartQA: Benchmarking Vision-Language Models on Multi-Chart ProblemsCode1
Help Me Identify: Is an LLM+VQA System All We Need to Identify Visual Concepts?Code0
Improving Multi-modal Large Language Model through Boosting Vision Capabilities—0
H2OVL-Mississippi Vision Language Models Technical Report—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