mlsanityData to 7 Oct 2026

Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature

arXiv 2305.11033 ↗First posted 18 May 2023cs.CV cs.AI cs.LGcited by 20

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Abstract (arXiv)

Visual Question Answering (VQA) is an emerging area of interest for researches, being a recent problem in natural language processing and image prediction. In this area, an algorithm needs to answer questions about certain images. As of the writing of this survey, 25 recent studies were analyzed. Besides, 6 datasets were analyzed and provided their link to download. In this work, several recent pieces of research in this area were investigated and a deeper analysis and comparison among them were provided, including results, the state-of-the-art, common errors, and possible points of improvement for future researchers.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 74 of its 107 references that are in the map. First posted on arXiv 18 May 2023.

Builds on

74 of 107 references.

References · 74

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38 more
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Citing papers per year: 2023: 3; 2024: 11; 2025: 5; 2026: 1.

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  1. 2024Natural Language Understanding and Inference with MLLM in Visual Question Answering: A Surveycited by 74
  2. 2024Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language Modelscited by 43
  3. 2024A Survey on Generative AI and LLM for Video Generation, Understanding, and Streamingcited by 37
  4. 2024Unveiling Visual Perception in Language Models: An Attention Head Analysis Approachcited by 34
  5. 2025CAFe: Unifying Representation and Generation with Contrastive-Autoregressive Finetuningcited by 31
  6. 2023Robust Visual Question Answering: Datasets, Methods, and Future Challengescited by 23
  7. 2023Multimodality of AI for Education: Towards Artificial General Intelligencecited by 21
  8. 2024Joint Visual and Text Prompting for Improved Object-Centric Perception with Multimodal Large Language Modelscited by 16
  9. 2024Knowledge-Aware Reasoning over Multimodal Semi-structured Tablescited by 9
  10. 2024Navigating the Landscape of Hint Generation Research: From the Past to the Futurecited by 6
  11. 2024ECOR: Explainable CLIP for Object Recognitioncited by 4
  12. 2024Can Visual Language Models Replace OCR-Based Visual Question Answering Pipelines in Production? A Case Study in Retailcited by 4
8 more
  1. 2024VolDoGer: LLM-assisted Datasets for Domain Generalization in Vision-Language Taskscited by 3
  2. 2025Watch Out Your Album! On the Inadvertent Privacy Memorization in Multi-Modal Large Language Modelscited by 3
  3. 2025CrafText Benchmark: Advancing Instruction Following in Complex Multimodal Open-Ended Worldcited by 2
  4. 2026TechING: Towards Real World Technical Image Understanding via VLMscited by 2
  5. 2024SparrowVQE: Visual Question Explanation for Course Content Understandingcited by 1
  6. 2023Superpixel Semantics Representation and Pre-training for Vision-Language Taskcited by 0
  7. 2025Robusto-1 Dataset: Comparing Humans and VLMs on real out-of-distribution Autonomous Driving VQA from Perucited by 0
  8. 2025GC-KBVQA: A New Four-Stage Framework for Enhancing Knowledge Based Visual Question Answering Performancecited by 0