On the public citation graph
Visual Question Answering: A Survey of Methods, Datasets, Evaluation, and Challenges
0 signed · 147 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cae.22388openalex-snapshot
Knowledge mapping of computer applications in education using CiteSpace
inferredcites →https://doi.org/10.1007/978-0-85729-859-1openalex-snapshot
Handbook of Document Image Processing and Recognition
inferredcites →https://doi.org/10.1007/978-3-030-01246-5_29openalex-snapshot
Question-Guided Hybrid Convolution for Visual Question Answering
inferredcites →https://doi.org/10.1007/978-3-030-30645-8_27openalex-snapshot
A Saliency-Based Convolutional Neural Network for Table and Chart Detection in Digitized Documents
inferredcites →https://doi.org/10.1007/978-3-030-32251-9_57openalex-snapshot
Overcoming Data Limitation in Medical Visual Question Answering
inferredcites →https://doi.org/10.1007/978-3-030-58601-0_2openalex-snapshot
Reducing Language Biases in Visual Question Answering with Visually-Grounded Question Encoder
inferredcites →https://doi.org/10.1007/978-3-031-20059-5_38openalex-snapshot
Webly Supervised Concept Expansion for General Purpose Vision Models
inferredcites →https://doi.org/10.1007/978-3-031-20074-8_9openalex-snapshot
A-OKVQA: A Benchmark for Visual Question Answering Using World Knowledge
inferredcites →https://doi.org/10.1007/978-3-031-72661-3_8openalex-snapshot
HYDRA: A Hyper Agent for Dynamic Compositional Visual Reasoning
inferredcites →https://doi.org/10.1007/978-3-031-73383-3_25openalex-snapshot
Multi-label Cluster Discrimination for Visual Representation Learning
inferredcites →https://doi.org/10.1007/978-3-031-78495-8_2openalex-snapshot
Visual Question Answering with Cascade of Self- and Co-Attention Blocks
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot
Microsoft COCO: Common Objects in Context
inferredcites →https://doi.org/10.1007/978-3-319-98932-7_28openalex-snapshot
Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation
inferredcites →https://doi.org/10.1007/978-3-642-33715-4_54openalex-snapshot
Indoor Segmentation and Support Inference from RGBD Images
inferredcites →https://doi.org/10.1007/s11042-024-18871-zopenalex-snapshot
Advanced Visual and Textual Co-context Aware Attention Network with Dependent Multimodal Fusion Block for Visual Question Answering
inferredcites →https://doi.org/10.1007/s11227-023-05195-2openalex-snapshot
Pre-trained multilevel fuse network based on vision-conditioned reasoning and bilinear attentions for medical image visual question answering
inferredcites →https://doi.org/10.1007/s11263-016-0981-7openalex-snapshot
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
inferredcites →https://doi.org/10.1016/j.artmed.2023.102611openalex-snapshot
Medical visual question answering: A survey
inferredcites →https://doi.org/10.1016/j.cviu.2017.05.001openalex-snapshot
Visual question answering: A survey of methods and datasets
inferredcites →https://doi.org/10.1016/j.eswa.2020.113993openalex-snapshot
Hierarchical deep multi-modal network for medical visual question answering
inferredcites →https://doi.org/10.1016/j.imavis.2021.104327openalex-snapshot
A survey of methods, datasets and evaluation metrics for visual question answering
inferredcites →https://doi.org/10.1016/j.inffus.2019.03.005openalex-snapshot
Information fusion in visual question answering: A Survey
inferredcites →https://doi.org/10.1016/j.inffus.2021.02.022openalex-snapshot
Multimodal feature-wise co-attention method for visual question answering
inferredcites →https://doi.org/10.1016/j.knosys.2020.106639openalex-snapshot
Multimodal deep fusion for image question answering
inferredcites →https://doi.org/10.1016/j.neucom.2020.03.098openalex-snapshot
Selective residual learning for Visual Question Answering
inferredcites →https://doi.org/10.1038/sdata.2018.251openalex-snapshot
A dataset of clinically generated visual questions and answers about radiology images
inferredcites →https://doi.org/10.1109/cvpr.1993openalex-snapshot
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
inferredcites →https://doi.org/10.1109/cvpr.2015.7298878openalex-snapshot
Long-term recurrent convolutional networks for visual recognition and description
inferredcites →https://doi.org/10.1109/cvpr.2015.7299087openalex-snapshot
CIDEr: Consensus-based image description evaluation
inferredcites →https://doi.org/10.1109/cvpr.2016.10openalex-snapshot
Stacked Attention Networks for Image Question Answering
inferredcites →https://doi.org/10.1109/cvpr.2016.499openalex-snapshot
Where to Look: Focus Regions for Visual Question Answering
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.123openalex-snapshot
Automatic Understanding of Image and Video Advertisements
inferredcites →https://doi.org/10.1109/cvpr.2017.153openalex-snapshot
Deep 360 Pilot: Learning a Deep Agent for Piloting through 360° Sports Videos
inferredcites →https://doi.org/10.1109/cvpr.2017.215openalex-snapshot
CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning
inferredcites →https://doi.org/10.1109/cvpr.2017.232openalex-snapshot
Dual Attention Networks for Multimodal Reasoning and Matching
inferredcites →https://doi.org/10.1109/cvpr.2017.670openalex-snapshot
Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering
inferredcites →https://doi.org/10.1109/cvpr.2018.00380openalex-snapshot
VizWiz Grand Challenge: Answering Visual Questions from Blind People
inferredcites →https://doi.org/10.1109/cvpr.2018.00522openalex-snapshot
Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering
inferredcites →https://doi.org/10.1109/cvpr.2018.00636openalex-snapshot
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
inferredcites →https://doi.org/10.1109/cvpr.2018.00637openalex-snapshot
Improved Fusion of Visual and Language Representations by Dense Symmetric Co-attention for Visual Question Answering
inferredcites →https://doi.org/10.1109/cvpr.2019.00103openalex-snapshot
VizWiz-Priv: A Dataset for Recognizing the Presence and Purpose of Private Visual Information in Images Taken by Blind People
inferredcites →https://doi.org/10.1109/cvpr.2019.00331openalex-snapshot
OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge
inferredcites →https://doi.org/10.1109/cvpr.2019.00644openalex-snapshot
Deep Modular Co-Attention Networks for Visual Question Answering
inferredcites →https://doi.org/10.1109/cvpr.2019.00686openalex-snapshot
GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering
inferredcites →https://doi.org/10.1109/cvpr35066.2017openalex-snapshot
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00998openalex-snapshot
Say As You Wish: Fine-Grained Control of Image Caption Generation With Abstract Scene Graphs
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01081openalex-snapshot
Counterfactual Samples Synthesizing for Robust Visual Question Answering
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01389openalex-snapshot
KRISP: Integrating Implicit and Symbolic Knowledge for Open-Domain Knowledge-Based VQA
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00135openalex-snapshot
Masked-attention Mask Transformer for Universal Image Segmentation
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00294openalex-snapshot
Invariant Grounding for Video Question Answering
inferredcites →https://doi.org/10.1109/cvpr52729.2023.01438openalex-snapshot
Prompting Large Language Models with Answer Heuristics for Knowledge-Based Visual Question Answering
inferredcites →https://doi.org/10.1109/cvpr52729.2023.01838openalex-snapshot
Image as a Foreign Language: BEIT Pretraining for Vision and Vision-Language Tasks
inferredcites →https://doi.org/10.1109/cvpr52729.2023.01845openalex-snapshot
Unifying Vision, Text, and Layout for Universal Document Processing
inferredcites →https://doi.org/10.1109/cvpr52733.2024.00461openalex-snapshot
Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks
inferredcites →https://doi.org/10.1109/cvpr52733.2024.00916openalex-snapshot
Visual Program Distillation: Distilling Tools and Programmatic Reasoning into Vision-Language Models
inferredcites →https://doi.org/10.1109/cvpr52733.2024.01347openalex-snapshot
Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-Rank Experts
inferredcites →https://doi.org/10.1109/cvprw53098.2021.00181openalex-snapshot
An Improved Attention for Visual Question Answering
inferredcites →https://doi.org/10.1109/cvprw56347.2022.00502openalex-snapshot
Coarse-to-Fine Reasoning for Visual Question Answering
inferredcites →https://doi.org/10.1109/iccv.1995.466933openalex-snapshot
Proceedings of IEEE International Conference on Computer Vision
inferredcites →https://doi.org/10.1109/iccv.2015.9openalex-snapshot
Ask Your Neurons: A Neural-Based Approach to Answering Questions about Images
inferredcites →https://doi.org/10.1109/iccv.2017.217openalex-snapshot
An Analysis of Visual Question Answering Algorithms
inferredcites →https://doi.org/10.1109/iccv.2017.74openalex-snapshot
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
inferredcites →https://doi.org/10.1109/iccv.2019.00439openalex-snapshot
Scene Text Visual Question Answering
inferredcites →https://doi.org/10.1109/iccv.2019.00898openalex-snapshot
Reflective Decoding Network for Image Captioning
inferredcites →https://doi.org/10.1109/iccv.2019.01039openalex-snapshot
Language-Conditioned Graph Networks for Relational Reasoning
inferredcites →https://doi.org/10.1109/iccv48922.2021.00161openalex-snapshot
Greedy Gradient Ensemble for Robust Visual Question Answering
inferredcites →https://doi.org/10.1109/iccv48922.2021.00180openalex-snapshot
MDETR - Modulated Detection for End-to-End Multi-Modal Understanding
inferredcites →https://doi.org/10.1109/iccv48922.2021.00189openalex-snapshot
Interpretable Visual Reasoning via Induced Symbolic Space
inferredcites →https://doi.org/10.1109/iccv51070.2023.00355openalex-snapshot
Adding Conditional Control to Text-to-Image Diffusion Models
inferredcites →https://doi.org/10.1109/icdar.2019.00156openalex-snapshot
OCR-VQA: Visual Question Answering by Reading Text in Images
inferredcites →https://doi.org/10.1109/isbi48211.2021.9434010openalex-snapshot
Slake: A Semantically-Labeled Knowledge-Enhanced Dataset For Medical Visual Question Answering
inferredcites →https://doi.org/10.1109/tnnls.2021.3104937openalex-snapshot
Bilinear Graph Networks for Visual Question Answering
inferredcites →https://doi.org/10.1109/tpami.2018.2798607openalex-snapshot
Multimodal Machine Learning: A Survey and Taxonomy
inferredcites →https://doi.org/10.1109/wacv.2019.00082openalex-snapshot
SPaSe - Multi-Label Page Segmentation for Presentation Slides
inferredcites →https://doi.org/10.1109/wacv48630.2021.00225openalex-snapshot
DocVQA: A Dataset for VQA on Document Images
inferredcites →https://doi.org/10.1145/3444685.3446256openalex-snapshot
Distilling knowledge in causal inference for unbiased visual question answering
inferredcites →https://doi.org/10.1609/aaai.v31i1.11197openalex-snapshot
Attention Correctness in Neural Image Captioning
inferredcites →https://doi.org/10.1609/aaai.v32i1.11671openalex-snapshot
FiLM: Visual Reasoning with a General Conditioning Layer
inferredcites →https://doi.org/10.1609/aaai.v32i1.12272openalex-snapshot
Exploring Human-Like Attention Supervision in Visual Question Answering
inferredcites →https://doi.org/10.1609/aaai.v36i3.20215openalex-snapshot
An Empirical Study of GPT-3 for Few-Shot Knowledge-Based VQA
inferredcites →https://doi.org/10.1609/aaai.v37i11.26598openalex-snapshot
SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images
inferredcites →https://doi.org/10.18653/v1/2020.bionlp-1openalex-snapshot
Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing
inferredcites →https://doi.org/10.18653/v1/2020.bionlp-1.6openalex-snapshot
Towards Visual Dialog for Radiology
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.44openalex-snapshot
ConceptBert: Concept-Aware Representation for Visual Question Answering
inferredcites →https://doi.org/10.18653/v1/2021.acl-long.201openalex-snapshot
LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding
inferredcites →https://doi.org/10.18653/v1/2022.emnlp-main.45openalex-snapshot
Crossmodal-3600: A Massively Multilingual Multimodal Evaluation Dataset
inferredcites →https://doi.org/10.18653/v1/2022.emnlp-main.481openalex-snapshot
FLUTE: Figurative Language Understanding through Textual Explanations
inferredcites →https://doi.org/10.18653/v1/2022.findings-acl.196openalex-snapshot
xGQA: Cross-Lingual Visual Question Answering
inferredcites →https://doi.org/10.18653/v1/2022.findings-emnlp.67openalex-snapshot
Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training
inferredcites →https://doi.org/10.18653/v1/2022.flp-1openalex-snapshot
Proceedings of the 3rd Workshop on Figurative Language Processing (FLP)
inferredcites →https://doi.org/10.18653/v1/2022.flp-1.20openalex-snapshot
SBU Figures It Out: Models Explain Figurative Language
inferredcites →https://doi.org/10.18653/v1/2023.acl-long.714openalex-snapshot
MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering
inferredcites →https://doi.org/10.18653/v1/2023.emnlp-industry.65openalex-snapshot
DUBLIN: Visual Document Understanding By Language-Image Network
inferredcites →https://doi.org/10.18653/v1/2023.findings-emnlp.176openalex-snapshot
MaXM: Towards Multilingual Visual Question Answering
inferredcites →https://doi.org/10.18653/v1/2023.findings-emnlp.40openalex-snapshot
Toward Building General Foundation Models for Language, Vision, and Vision-Language Understanding Tasks
inferredcites →https://doi.org/10.18653/v1/d16-1044openalex-snapshot
Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding
inferredcites →https://doi.org/10.18653/v1/d16-1203openalex-snapshot
Analyzing the Behavior of Visual Question Answering Models
inferredcites →https://doi.org/10.18653/v1/d18-2029openalex-snapshot
Universal Sentence Encoder for English
inferredcites →https://doi.org/10.18653/v1/d19-1418openalex-snapshot
Don’t Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases
inferredcites →https://doi.org/10.18653/v1/d19-1514openalex-snapshot
LXMERT: Learning Cross-Modality Encoder Representations from Transformers
inferredcites →https://doi.org/10.18653/v1/p16-2openalex-snapshot
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
inferredcites →https://doi.org/10.18653/v1/p17-2034openalex-snapshot
A Corpus of Natural Language for Visual Reasoning
inferredcites →https://doi.org/10.18653/v1/p18-1238openalex-snapshot
Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning
inferredcites →https://doi.org/10.18653/v1/p19-1644openalex-snapshot
A Corpus for Reasoning about Natural Language Grounded in Photographs
inferredcites →https://doi.org/10.24963/ijcai.2017/371openalex-snapshot
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations
inferredcites →https://doi.org/10.24963/ijcai.2024/339openalex-snapshot
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
inferredcites →https://doi.org/10.32604/jbd.2021.017169openalex-snapshot
WMA: A Multi-Scale Self-Attention Feature Extraction Network Based on Weight Sharing for VQA
inferredcites →https://doi.org/10.3390/s22031045openalex-snapshot
Deep Modular Bilinear Attention Network for Visual Question Answering
inferredcites →https://doi.org/10.48550/arxiv.2204.14198openalex-snapshot
Flamingo: a Visual Language Model for Few-Shot Learning
inferredcites →https://doi.org/10.48550/arxiv.2410.12705openalex-snapshot
WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines
inferredcites →https://doi.org/10.52202/068431-0767openalex-snapshot
REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering
inferredcites →https://doi.org/10.52202/068431-2384openalex-snapshot
VLMo: Unified Vision-Language Pre-Training with Mixture-Of-Modality-Experts
inferredcites →https://doi.org/10.5244/c.28.6openalex-snapshot
Return of the Devil in the Details: Delving Deep into Convolutional Nets
inferredcites →https://doi.org/10.7717/peerj-cs.1400openalex-snapshot
The multi-modal fusion in visual question answering: a review of attention mechanisms
inferredcites →https://doi.org/10.7717/peerj-cs.353openalex-snapshot
Joint embedding VQA model based on dynamic word vector
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-981-95-6963-2_26openalex-snapshot
NII-UIT at VBS2026: Towards Effective Visual Question Answering for Interactive and Multimodal Video Retrieval
inferred← citeshttps://doi.org/10.1007/s11760-025-04710-7openalex-snapshot
Enhancing VQA with Emphasis-Based Soft Attention
inferred← citeshttps://doi.org/10.1007/s12065-026-01259-3openalex-snapshot
Intelligent agents: architectures, learning paradigms, deployment models, and applications
inferred← citeshttps://doi.org/10.1007/s12204-026-2947-4openalex-snapshot
FaithRAG: Retrieval-Augmented Generation for Faithful Video Understanding
inferred← citeshttps://doi.org/10.1016/j.ins.2026.123989openalex-snapshot
Decoupled multimodal representation learning for robust VQA
inferred← citeshttps://doi.org/10.1061/jccee5.cpeng-7571openalex-snapshot
ArchPlanVQA: Benchmark and Comprehensive Evaluation of Vision-Language Models for Understanding Architectural Floor Plan CAD Drawings
inferred← citeshttps://doi.org/10.1109/access.2026.3654676openalex-snapshot
Visual Question Answering for Intelligent Communication Systems: A Systematic Review
inferred← citeshttps://doi.org/10.1109/cscwd68734.2026.11581733openalex-snapshot
SynaLumi: An Embodied Intelligence Interaction System for the Blind or Low-Vision Populations Based on Large Multimodal Models
inferred← citeshttps://doi.org/10.1109/dlcv69906.2026.11635196openalex-snapshot
SHARP: A Multimodal Vision-Language Active Learning Framework for Cold-Start Image Retrieval
inferred← citeshttps://doi.org/10.1109/healthcom60686.2025.11342571openalex-snapshot
The Impact of Thinking Mode and Multimodal Analysis on Generative AI’s Assessment of Medical Videos
inferred← citeshttps://doi.org/10.1109/iaict71158.2026.11620852openalex-snapshot
A Comparative Study of Lightweight Vision-Language Models for Visual Question Answering Under Visual Degradation and Prompt Engineering
inferred← citeshttps://doi.org/10.1109/icassp55912.2026.11464013openalex-snapshot
Plug-and-Play Robust Vision Encoders for Multi-Modal Large Language Models Via Fully Multi-Modal Adversarial Finetuning
inferred← citeshttps://doi.org/10.1109/iccit68739.2025.11491619openalex-snapshot
Bangla Visual Question Answering Using Gated Cross-Attention and Reinforcement-Optimized Fusion
inferred← citeshttps://doi.org/10.1109/icdmw69685.2025.00167openalex-snapshot
TALENT: Table VQA via Augmented Language-Enhanced Natural-Text Transcription
inferred← citeshttps://doi.org/10.1109/iceaai68945.2026.11442542openalex-snapshot
Reliability Analysis of AI-Enhanced Multimodal Assistive Systems for in-Home Elderly Care
inferred← citeshttps://doi.org/10.1109/iceic69189.2026.11386008openalex-snapshot
GDE: Grid-based Diversity Enhancement for Efficient Vision Token Selection in VLMs
inferred← citeshttps://doi.org/10.1109/iconscept66142.2025.11437368openalex-snapshot
Enhancing Chart Question Answering Using Multimodal Reasoning Techniques
inferred← citeshttps://doi.org/10.1109/iicaiet67254.2025.11265486openalex-snapshot
Toward Semantic Communication in 6G: A Multimodal Perspective Based on Visual Question Answering Systems
inferred← citeshttps://doi.org/10.1109/sccc67219.2025.11420451openalex-snapshot
No-Reference Evaluation for Visual Question Answering using Large Language Models and Semi-supervised Learning
inferred← citeshttps://doi.org/10.1109/taslpro.2026.3675784openalex-snapshot
Alleviating Contextual Misguidance: Response-Aware Prompt Compression for Long-Context Question Answering
inferred← citeshttps://doi.org/10.1145/3788861openalex-snapshot
VisionAidQA: Advancing Visual Question Answering for the Visually Impaired
inferred← citeshttps://doi.org/10.1145/3805622.3810578openalex-snapshot
Adaptive Knowledge Generation via Reinforcement-Guided Pattern Completion for Zero-Shot Visual Question Answering
inferred← citeshttps://doi.org/10.1145/3805622.3810597openalex-snapshot
Ask-to-Retrieve: VQA-Guided Information-Gain Question Selection for Interactive Text-to-Image Retrieval
inferred← citeshttps://doi.org/10.1145/3805622.3810807openalex-snapshot
Beyond Inconsistent Reasoning: Intermediate Process Direct Preference Optimization on Small Multi-modal Large Language Models for Visual Question Answering
inferred← citeshttps://doi.org/10.2139/ssrn.7417407openalex-snapshot
Visual Question Answering: A Survey on Architectures, Datasets, Evaluation Metrics and Applications
inferred← citeshttps://doi.org/10.3390/ai7090367openalex-snapshot
A Survey of Visual Question Answering for Embodied Robots: Tasks, Methods, and Future Directions
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.