mlsanityData to 14 Oct 2026

VQA Therapy: Exploring Answer Differences by Visually Grounding Answers

arXiv 2308.11662 ↗First posted 21 Aug 2023cs.CVcited by 14

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Abstract (arXiv)

Visual question answering is a task of predicting the answer to a question about an image. Given that different people can provide different answers to a visual question, we aim to better understand why with answer groundings. We introduce the first dataset that visually grounds each unique answer to each visual question, which we call VQAAnswerTherapy. We then propose two novel problems of predicting whether a visual question has a single answer grounding and localizing all answer groundings. We benchmark modern algorithms for these novel problems to show where they succeed and struggle. The dataset and evaluation server can be found publicly at https://vizwiz.org/tasks-and-datasets/vqa-answer-therapy/.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 29 of its 35 references that are in the map. First posted on arXiv 21 Aug 2023.

Builds on

29 of 35 references.

References · 29

  1. 2016Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotationscited by 2,656
  2. 2016Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answeringcited by 2,516
  3. 2015VQA: Visual Question Answeringcited by 2,506
  4. 2019Towards VQA Models That Can Readcited by 1,718
  5. 2015Microsoft COCO Captions: Data Collection and Evaluation Servercited by 1,462
  6. 2015Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Modelscited by 1,362
  7. 2021ViLT: Vision-and-Language Transformer Without Convolution or Region Supervisioncited by 1,230
  8. 2016Modeling Context in Referring Expressionscited by 1,063
  9. 2023mPLUG-Owl: Modularization Empowers Large Language Models with Multimodalitycited by 1,040
  10. 2015Generation and Comprehension of Unambiguous Object Descriptionscited by 904
  11. 2018VizWiz Grand Challenge: Answering Visual Questions from Blind Peoplecited by 858
  12. 2023Segment Everything Everywhere All at Oncecited by 548
17 more
  1. 2015Visual7W: Grounded Question Answering in Imagescited by 318
  2. 2016Modeling Context Between Objects for Referring Expression Understandingcited by 251
  3. 2023Universal Instance Perception as Object Discovery and Retrievalcited by 192
  4. 2018Multimodal Explanations: Justifying Decisions and Pointing to the Evidencecited by 179
  5. 2022SeqTR: A Simple yet Universal Network for Visual Groundingcited by 139
  6. 2020PhraseCut: Language-based Image Segmentation in the Wildcited by 116
  7. 2016Human Attention in Visual Question Answering: Do Humans and Deep Networks Look at the Same Regions?cited by 111
  8. 2017VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentationcited by 50
  9. 2022Grounding Answers for Visual Questions Asked by Visually Impaired Peoplecited by 47
  10. 2019Why Does a Visual Question Have Different Answers?cited by 34
  11. 2018Interpretable Visual Question Answering by Visual Grounding from Attention Supervision Miningcited by 28
  12. 2020AiR: Attention with Reasoning Capabilitycited by 28
  13. 2021Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsulescited by 22
  14. 2020Vision Skills Needed to Answer Visual Questionscited by 17
  15. 2021A First Look: Towards Explainable TextVQA Models via Visual and Textual Explanationscited by 14
  16. 2022Why Did the Chicken Cross the Road? Rephrasing and Analyzing Ambiguous Questions in VQAcited by 13
  17. 2022REX: Reasoning-aware and Grounded Explanationcited by 12

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Citing papers per year: 2024: 5; 2025: 6; 2026: 3.

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  1. 2024Long-Form Answers to Visual Questions from Blind and Low Vision Peoplecited by 18
  2. 2025Evaluating Multimodal Language Models as Visual Assistants for Visually Impaired Userscited by 11
  3. 2025RefChartQA: Grounding Visual Answer on Chart Images through Instruction Tuningcited by 11
  4. 2025Towards Understanding Visual Grounding in Visual Language Modelscited by 10
  5. 2025Acknowledging Focus Ambiguity in Visual Questionscited by 8
  6. 2024Selectively Answering Visual Questionscited by 5
  7. 2024Scene-Text Grounding for Text-Based Video Question Answeringcited by 5
  8. 2026Evaluating Cross-Modal Reasoning Ability and Problem Characteristics with Multimodal Item Response Theorycited by 3
  9. 2025BLaVe-CoT: Consistency-Aware Visual Question Answering for Blind and Low Vision Userscited by 1
  10. 2024StackOverflowVQA: Stack Overflow Visual Question Answering Datasetcited by 0
  11. 2024Second Place Solution of WSDM2023 Toloka Visual Question Answering Challengecited by 0
  12. 2025Hierarchical Instance Tracking to Balance Privacy Preservation with Accessible Informationcited by 0
2 more
  1. 2026Explicit Logic Channel for Validation and Enhancement of MLLMs on Zero-Shot Taskscited by 0
  2. 2026Multimodal Plant Root Phenotyping with Integration of 3D Skeleton Extraction and Language Analysiscited by 0