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Visual Question Answering

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Showing 1601–1650 of 2177 papers

TitleStatusHype
Question Generation for Evaluating Cross-Dataset Shifts in Multi-modal Grounding—0
Probing the Role of Positional Information in Vision-Language Models—0
Task Formulation Matters When Learning Continuously: A Case Study in Visual Question Answering—0
MANGO: Enhancing the Robustness of VQA Models via Adversarial Noise Generation—0
Retrieving Visual Facts For Few-Shot Visual Question Answering—0
All You May Need for VQA are Image Captions—0
CLIP-TD: CLIP Targeted Distillation for Vision-Language Tasks—0
A Thousand Words Are Worth More Than a Picture: Natural Language-Centric Outside-Knowledge Visual Question Answering—0
Towards Automated Error Analysis: Learning to Characterize Errors—0
On the Efficacy of Co-Attention Transformer Layers in Visual Question Answering—0
Uni-EDEN: Universal Encoder-Decoder Network by Multi-Granular Vision-Language Pre-training—0
COIN: Counterfactual Image Generation for VQA Interpretation—0
Interactive Attention AI to translate low light photos to captions for night scene understanding in women safety—0
Query and Attention Augmentation for Knowledge-Based Explainable ReasoningCode0
V-Doc: Visual Questions Answers With Documents—0
Transform-Retrieve-Generate: Natural Language-Centric Outside-Knowledge Visual Question Answering—0
Towards General Purpose Vision Systems: An End-to-End Task-Agnostic Vision-Language Architecture—0
Does CLIP Benefit Visual Question Answering in the Medical Domain as Much as it Does in the General Domain?—0
Multi-Image Visual Question AnsweringCode0
General Greedy De-bias LearningCode0
Task-Oriented Multi-User Semantic Communications—0
Understanding Attention for Vision-and-Language Tasks—0
3D Question Answering—0
Improving and Diagnosing Knowledge-Based Visual Question Answering via Entity Enhanced Knowledge Injection—0
Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation—0
MoCA: Incorporating Multi-stage Domain Pretraining and Cross-guided Multimodal Attention for Textbook Question Answering—0
eaVQA: An Experimental Analysis on Visual Question Answering Models—0
Curriculum Learning Effectively Improves Low Data VQA—0
Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning—0
Robust Visual Reasoning via Language Guided Neural Module Networks—0
Scene Graph Generation with Geometric Context—0
A Confidence-Based Interface for Neuro-Symbolic Visual Question Answering—0
Medical Visual Question Answering: A Survey—0
UFO: A UniFied TransfOrmer for Vision-Language Representation Learning—0
Achieving Human Parity on Visual Question Answering—0
ViQuAE, a Dataset for Knowledge-based Visual Question Answering about Named EntitiesCode0
Language bias in Visual Question Answering: A Survey and Taxonomy—0
Enabling Multimodal Generation on CLIP via Vision-Language Knowledge Distillation—0
Question-Led Semantic Structure Enhanced Attentions for VQA—0
Document AI: Benchmarks, Models and Applications—0
Breaking Down Questions for Outside-Knowledge Visual Question Answering—0
Uncertainty-based Visual Question Answering: Estimating Semantic Inconsistency between Image and Knowledge Base—0
Co-VQA : Answering by Interactive Sub Question Sequence—0
Graph Relation Transformer: Incorporating pairwise object features into the Transformer architecture—0
Visual Question Answering based on Formal Logic—0
Diversity and Consistency: Exploring Visual Question-Answer Pair Generation—0
CrossVQA: Scalably Generating Benchmarks for Systematically Testing VQA Generalization—0
MIRTT: Learning Multimodal Interaction Representations from Trilinear Transformers for Visual Question AnsweringCode0
Perceptual Score: What Data Modalities Does Your Model Perceive?Code0
Alignment Attention by Matching Key and Query DistributionsCode0
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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