mlsanityData to 7 Oct 2026

Exploring Models and Data for Image Question Answering

arXiv 1505.02074 ↗First posted 8 May 2015cs.LG cs.AI cs.CLcited by 139

Not on the map. Why?

Cited by 29 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

This work aims to address the problem of image-based question-answering (QA) with new models and datasets. In our work, we propose to use neural networks and visual semantic embeddings, without intermediate stages such as object detection and image segmentation, to predict answers to simple questions about images. Our model performs 1.8 times better than the only published results on an existing image QA dataset. We also present a question generation algorithm that converts image descriptions, which are widely available, into QA form. We used this algorithm to produce an order-of-magnitude larger dataset, with more evenly distributed answers. A suite of baseline results on this new dataset are also presented.

Key facts. Cited by 139 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 May 2015.

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Citing papers per year: 2021: 19; 2022: 26; 2023: 38; 2024: 26; 2025: 22; 2026: 8.

139 papers.

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  1. 2022A-OKVQA: A Benchmark for Visual Question Answering using World Knowledgecited by 702
  2. 2024What matters when building vision-language models?cited by 321
  3. 2024Building and better understanding vision-language models: insights and future directionscited by 169
  4. 2024MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scalecited by 125
  5. 2023Encyclopedic VQA: Visual questions about detailed properties of fine-grained categoriescited by 105
  6. 2022Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoningcited by 90
  7. 2021SUTD-TrafficQA: A Question Answering Benchmark and an Efficient Network for Video Reasoning over Traffic Eventscited by 84
  8. 2023Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Modelscited by 80
  9. 2024Natural Language Understanding and Inference with MLLM in Visual Question Answering: A Surveycited by 74
  10. 2022All You May Need for VQA are Image Captionscited by 65
  11. 2021Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answeringcited by 62
  12. 2023Towards Vision-Language Mechanistic Interpretability: A Causal Tracing Tool for BLIPcited by 62
38 more
  1. 2023FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learningcited by 59
  2. 2022Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answeringcited by 57
  3. 2023SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMscited by 54
  4. 2025FineVision: Open Data Is All You Needcited by 51
  5. 2024Elysium: Exploring Object-level Perception in Videos via MLLMcited by 48
  6. 20213D Question Answeringcited by 41
  7. 2022Deep Learning Methods for Abstract Visual Reasoning: A Survey on Raven's Progressive Matricescited by 37
  8. 2024SOLO: A Single Transformer for Scalable Vision-Language Modelingcited by 35
  9. 2021Multimodal Dialogue Response Generationcited by 32
  10. 2021ArchivalQA: A Large-scale Benchmark Dataset for Open Domain Question Answering over Historical News Collectionscited by 30
  11. 2022PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Taskscited by 30
  12. 2022Learning to Answer Visual Questions from Web Videoscited by 30
  13. 2022A Review on Methods and Applications in Multimodal Deep Learningcited by 29
  14. 2022Vision-Language Intelligence: Tasks, Representation Learning, and Large Modelscited by 28
  15. 2021Recent Advances and Trends in Multimodal Deep Learning: A Reviewcited by 26
  16. 2023From Image to Language: A Critical Analysis of Visual Question Answering (VQA) Approaches, Challenges, and Opportunitiescited by 24
  17. 2023UNK-VQA: A Dataset and a Probe into the Abstention Ability of Multi-modal Large Modelscited by 23
  18. 2024Beyond Text: Frozen Large Language Models in Visual Signal Comprehensioncited by 23
  19. 2023Tem-adapter: Adapting Image-Text Pretraining for Video Question Answercited by 22
  20. 2026LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decodingcited by 20
  21. 2021MuMuQA: Multimedia Multi-Hop News Question Answering via Cross-Media Knowledge Extraction and Groundingcited by 19
  22. 2025M2-omni: Advancing Omni-MLLM for Comprehensive Modality Support with Competitive Performancecited by 19
  23. 2021Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matricescited by 17
  24. 2023Foundation Model is Efficient Multimodal Multitask Model Selectorcited by 16
  25. 20233D-Aware Visual Question Answering about Parts, Poses and Occlusionscited by 16
  26. 2024EfficientEQA: An Efficient Approach to Open-Vocabulary Embodied Question Answeringcited by 15
  27. 2024Show Me What and Where has Changed? Question Answering and Grounding for Remote Sensing Change Detectioncited by 15
  28. 2021CLEVR_HYP: A Challenge Dataset and Baselines for Visual Question Answering with Hypothetical Actions over Imagescited by 14
  29. 2021Asking questions on handwritten document collectionscited by 14
  30. 2022A Neuro-Symbolic ASP Pipeline for Visual Question Answeringcited by 14
  31. 2022VQA and Visual Reasoning: An Overview of Recent Datasets, Methods and Challengescited by 14
  32. 2024Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Modelscited by 14
  33. 2025MindLLM: A Subject-Agnostic and Versatile Model for fMRI-to-Text Decodingcited by 14
  34. 2021GoG: Relation-aware Graph-over-Graph Network for Visual Dialogcited by 13
  35. 2024Towards Foundation Models for 3D Vision: How Close Are We?cited by 13
  36. 2023HaVQA: A Dataset for Visual Question Answering and Multimodal Research in Hausa Languagecited by 12
  37. 2024Grounding Language Models for Visual Entity Recognitioncited by 12
  38. 2021Domain-robust VQA with diverse datasets and methods but no target labelscited by 11

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