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Visual Question Answering

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Showing 1701–1750 of 2177 papers

TitleStatusHype
EaSe: A Diagnostic Tool for VQA based on Answer DiversityCode0
Learning to Select Question-Relevant Relations for Visual Question Answering—0
LPF: A Language-Prior Feedback Objective Function for De-biased Visual Question AnsweringCode0
StructuralLM: Structural Pre-training for Form Understanding—0
Probing Inter-modality: Visual Parsing with Self-Attention for Vision-and-Language Pre-training—0
Survey of Visual-Semantic Embedding Methods for Zero-Shot Image Retrieval—0
Show Why the Answer is Correct! Towards Explainable AI using Compositional Temporal Attention—0
Cross-Modal Generative Augmentation for Visual Question Answering—0
Proposal-free One-stage Referring Expression via Grid-Word Cross-Attention—0
AdaVQA: Overcoming Language Priors with Adapted Margin Cosine LossCode0
Iterated learning for emergent systematicity in VQA—0
A survey on VQA_Datasets and Approaches—0
Chop Chop BERT: Visual Question Answering by Chopping VisualBERT's Heads—0
Document Collection Visual Question Answering—0
InfographicVQA—0
Playing Lottery Tickets with Vision and Language—0
VGNMN: Video-grounded Neural Module Network to Video-Grounded Language Tasks—0
Cross-Modal Retrieval Augmentation for Multi-Modal Classification—0
Jointly Learning Truth-Conditional Denotations and Groundings using Parallel Attention—0
Neuro-Symbolic VQA: A review from the perspective of AGI desiderata—0
CLEVR_HYP: A Challenge Dataset and Baselines for Visual Question Answering with Hypothetical Actions over ImagesCode0
How Transferable are Reasoning Patterns in VQA?—0
Multimodal Continuous Visual Attention Mechanisms—0
Compressing Visual-linguistic Model via Knowledge Distillation—0
`Just because you are right, doesn't mean I am wrong': Overcoming a bottleneck in development and evaluation of Open-Ended VQA tasks—0
UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training—0
Analysis on Image Set Visual Question Answering—0
Domain-robust VQA with diverse datasets and methods but no target labels—0
'Just because you are right, doesn't mean I am wrong': Overcoming a Bottleneck in the Development and Evaluation of Open-Ended Visual Question Answering (VQA) TasksCode0
Generating and Evaluating Explanations of Attended and Error-Inducing Input Regions for VQA Models—0
Visual Grounding Strategies for Text-Only Natural Language Processing—0
How to Design Sample and Computationally Efficient VQA Models—0
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQACode0
A Comprehensive Survey of Scene Graphs: Generation and Application—0
Characterizing Misclassifications of Deep NLP Models—0
RL-CSDia: Representation Learning of Computer Science Diagrams—0
Select, Substitute, Search: A New Benchmark for Knowledge-Augmented Visual Question AnsweringCode0
Contextual Dropout: An Efficient Sample-Dependent Dropout ModuleCode0
Visual Question Answering: which investigated applications?Code0
Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialogues—0
Learning Compositional Representation for Few-shot Visual Question Answering—0
Answer Questions with Right Image Regions: A Visual Attention Regularization ApproachCode0
An Empirical Study on the Generalization Power of Neural Representations Learned via Visual Guessing Games—0
Unanswerable Questions about Images and Texts—0
Visual Question Answering based on Local-Scene-Aware Referring Expression Generation—0
Understanding in Artificial Intelligence—0
Latent Variable Models for Visual Question Answering—0
Understanding the Role of Scene Graphs in Visual Question Answering—0
Predicting Relative Depth between Objects from Semantic Features—0
Self Supervision for Attention NetworksCode0
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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