ArticlePeerJ. Computer science2023
The multi-modal fusion in visual question answering: a review of attention mechanisms.
Article in PeerJ. Computer science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Perception, assessment, and coaching: a systematic review and taxonomy of computer vision-based physical rehabilitation techniques.Frontiers in rehabilitation sciences · 2026Pooled it
- AdaFuse: Adaptive Multimodal Fusion for Lung Cancer Risk Prediction via Reinforcement Learning.Proceedings of machine learning research · 2026Article
- HMDF-Net: a transfer learning-based heterogeneous multimodal dynamic fusion network for depression detection among inmates in correctional facilities.Frontiers in psychiatry · 2026Article
- Multimodal sequence dynamics and convergence optimization in dual-stream LSTM networks for complex physiological state estimation.Frontiers in neurorobotics · 2026Article
- Multimodal artificial intelligence for subepithelial lesion classification and characterization: a multicenter comparative study (with video).BMC medical informatics and decision making · 2025Article
- Dense skip-attention for convolutional networks.Scientific reports · 2025Article
- Cognitive difference text classification in online knowledge collaboration based on SA-BiLSTM hybrid model.Scientific reports · 2025Article
- MDEU-Net: Medical Image Segmentation Network Based on Multi-Head Multi-Scale Cross-Axis.Sensors (Basel, Switzerland) · 2025Article
- A comprehensive framework for multi-modal hate speech detection in social media using deep learning.Scientific reports · 2025Article
- A novel arc detection and identification method in pantograph-catenary system based on deep learning.Scientific reports · 2025Article
- Physical-intellectual badminton teaching intervention for children with intellectual disabilities.Frontiers in psychology · 2025Article
- Hybrid deep learning models for text-based identification of gene-disease associations.BioImpacts : BI · 2025Article
- 3D-BCLAM: A Lightweight Neurodynamic Model for Assessing Student Learning Effectiveness.Sensors (Basel, Switzerland) · 2024Article
- A Deep Learning Model for Accurate Maize Disease Detection Based on State-Space Attention and Feature Fusion.Plants (Basel, Switzerland) · 2024Article
- Object Detection and Information Perception by Fusing YOLO-SCG and Point Cloud Clustering.Sensors (Basel, Switzerland) · 2024Article
- A Multi-Scale Natural Scene Text Detection Method Based on Attention Feature Extraction and Cascade Feature Fusion.Sensors (Basel, Switzerland) · 2024Article
- Adaptive habitat biogeography-based optimizer for optimizing deep CNN hyperparameters in image classification.Heliyon · 2024Article
- Joint analysis of interaction and psychological characteristics in english teaching based on multimodal integration.BMC psychology · 2024Article
- Determinants of the transition towards circular economy in SMEs: a sustainable supply chain management perspective.Environmental science and pollution research international · 2024Article
- Disciplinary measures defining referee activity in top-European football leagues: A cross-sectional investigation.Heliyon · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Visual Question Answering (VQA) is a significant cross-disciplinary issue in the fields of computer vision and natural language processing that requires a computer to output a natural language answer based on pictures and questions posed based on the pictures. This requires simultaneous processing of multimodal fusion of text features and visual features, and the key task that can ensure its success is the attention mechanism. Bringing in attention mechanisms makes it better to integrate text features and image features into a compact multi-modal representation. Therefore, it is necessary to clarify the development status of attention mechanism, understand the most advanced attention mechanism methods, and look forward to its future development direction. In this article, we first conduct a bibliometric analysis of the correlation through CiteSpace, then we find and reasonably speculate that the attention mechanism has great development potential in cross-modal retrieval. Secondly, we discuss the classification and application of existing attention mechanisms in VQA tasks, analysis their shortcomings, and summarize current improvement methods. Finally, through the continuous exploration of attention mechanisms, we believe that VQA will evolve in a smarter and more human direction.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.