mlsanityData to 14 Oct 2026

Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning

arXiv 2109.06860 ↗First posted 14 Sep 2021cs.CL cs.AI cs.CVcited by 59

Not on the map. Why?

Cited by 26 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Commonsense is defined as the knowledge that is shared by everyone. However, certain types of commonsense knowledge are correlated with culture and geographic locations and they are only shared locally. For example, the scenarios of wedding ceremonies vary across regions due to different customs influenced by historical and religious factors. Such regional characteristics, however, are generally omitted in prior work. In this paper, we construct a Geo-Diverse Visual Commonsense Reasoning dataset (GD-VCR) to test vision-and-language models' ability to understand cultural and geo-location-specific commonsense. In particular, we study two state-of-the-art Vision-and-Language models, VisualBERT and ViLBERT trained on VCR, a standard multimodal commonsense benchmark with images primarily from Western regions. We then evaluate how well the trained models can generalize to answering the questions in GD-VCR. We find that the performance of both models for non-Western regions including East Asia, South Asia, and Africa is significantly lower than that for Western region. We analyze the reasons behind the performance disparity and find that the performance gap is larger on QA pairs that: 1) are concerned with culture-related scenarios, e.g., weddings, religious activities, and festivals; 2) require high-level geo-diverse commonsense reasoning rather than low-order perception and recognition. Dataset and code are released at https://github.com/WadeYin9712/GD-VCR.

Key facts. Cited by 59 papers in the map (data through 14 Oct 2026). Builds on 22 of its 40 references that are in the map. First posted on arXiv 14 Sep 2021.

Builds on

22 of 40 references.

References · 22

  1. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  3. 2019PIQA: Reasoning about Physical Commonsense in Natural Languagecited by 2,883
  4. 2016Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answeringcited by 2,516
  5. 2015VQA: Visual Question Answeringcited by 2,506
  6. 2019ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Taskscited by 2,222
  7. 2018CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledgecited by 1,822
  8. 2015Microsoft COCO Captions: Data Collection and Evaluation Servercited by 1,462
  9. 2015Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Modelscited by 1,362
  10. 2019VisualBERT: A Simple and Performant Baseline for Vision and Languagecited by 1,296
  11. 2018From Recognition to Cognition: Visual Commonsense Reasoningcited by 556
  12. 2018A Corpus for Reasoning About Natural Language Grounded in Photographscited by 459
10 more
  1. 2018SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inferencecited by 333
  2. 2020XCOPA: A Multilingual Dataset for Causal Commonsense Reasoningcited by 333
  3. 2019Abductive Commonsense Reasoningcited by 301
  4. 2019Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoningcited by 285
  5. 2016Demographic Dialectal Variation in Social Media: A Case Study of African-American Englishcited by 196
  6. 2017No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing Worldcited by 153
  7. 2019Does Object Recognition Work for Everyone?cited by 151
  8. 2019"Going on a vacation" takes longer than "Going for a walk": A Study of Temporal Commonsense Understandingcited by 123
  9. 2021Common Sense Beyond English: Evaluating and Improving Multilingual Language Models for Commonsense Reasoningcited by 65
  10. 2020Towards an Atlas of Cultural Commonsense for Machine Reasoningcited by 29

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Citing papers per year: 2022: 13; 2023: 12; 2024: 18; 2025: 8; 2026: 8.

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  1. 2023MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contextscited by 1,614
  2. 2023The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)cited by 681
  3. 2022Challenges and Strategies in Cross-Cultural NLPcited by 218
  4. 2023VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Usecited by 102
  5. 2024Benchmarking Vision Language Models for Cultural Understandingcited by 101
  6. 2022On the Paradox of Learning to Reason from Datacited by 93
  7. 2022How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?cited by 92
  8. 2022Extracting Cultural Commonsense Knowledge at Scalecited by 76
  9. 2023KoBBQ: Korean Bias Benchmark for Question Answeringcited by 71
  10. 2023Natural Language Reasoning, A Surveycited by 61
  11. 2024All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languagescited by 55
  12. 2022IGLUE: A Benchmark for Transfer Learning across Modalities, Tasks, and Languagescited by 54
38 more
  1. 2024GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Taskscited by 51
  2. 2023Benchmarks for Automated Commonsense Reasoning: A Surveycited by 40
  3. 2022A Survey of Knowledge-Intensive NLP with Pre-Trained Language Modelscited by 30
  4. 2022GeoMLAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language Modelscited by 30
  5. 2022Square One Bias in NLP: Towards a Multi-Dimensional Exploration of the Research Manifoldcited by 29
  6. 2024Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Artcited by 26
  7. 2024Polymath: A Challenging Multi-modal Mathematical Reasoning Benchmarkcited by 22
  8. 2024Cultural Commonsense Knowledge for Intercultural Dialoguescited by 20
  9. 2024ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Modelscited by 19
  10. 2024Evaluating Visual and Cultural Interpretation: The K-Viscuit Benchmark with Human-VLM Collaborationcited by 19
  11. 2024No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Modelscited by 16
  12. 2024MMRo: Are Multimodal LLMs Eligible as the Brain for In-Home Robotics?cited by 15
  13. 2024Multilingual Diversity Improves Vision-Language Representationscited by 14
  14. 2024From Local Concepts to Universals: Evaluating the Multicultural Understanding of Vision-Language Modelscited by 14
  15. 2023GD-COMET: A Geo-Diverse Commonsense Inference Modelcited by 13
  16. 2022Answer-Me: Multi-Task Open-Vocabulary Visual Question Answeringcited by 12
  17. 2023Localized Symbolic Knowledge Distillation for Visual Commonsense Modelscited by 12
  18. 2023GIVL: Improving Geographical Inclusivity of Vision-Language Models with Pre-Training Methodscited by 11
  19. 2024Creating a Lens of Chinese Culture: A Multimodal Dataset for Chinese Pun Rebus Art Understandingcited by 11
  20. 2024CROPE: Evaluating In-Context Adaptation of Vision and Language Models to Culture-Specific Conceptscited by 11
  21. 2024SafeWorld: Geo-Diverse Safety Alignmentcited by 11
  22. 2024Susu Box or Piggy Bank: Assessing Cultural Commonsense Knowledge between Ghana and the U.Scited by 9
  23. 2024The Power of Many: Multi-Agent Multimodal Models for Cultural Image Captioningcited by 9
  24. 2024CIC: A Framework for Culturally-Aware Image Captioningcited by 8
  25. 2025IndicVisionBench: Benchmarking Cultural and Multilingual Understanding in VLMscited by 8
  26. 2022Counterfactual Recipe Generation: Exploring Compositional Generalization in a Realistic Scenariocited by 5
  27. 2023Flickr Africa: Examining Geo-Diversity in Large-Scale, Human-Centric Visual Datacited by 5
  28. 2025Hanfu-Bench: A Multimodal Benchmark on Cross-Temporal Cultural Understanding and Transcreationcited by 5
  29. 2022VIPHY: Probing "Visible" Physical Commonsense Knowledgecited by 4
  30. 2022COFAR: Commonsense and Factual Reasoning in Image Searchcited by 4
  31. 2025Mind the Gesture: Evaluating AI Sensitivity to Culturally Offensive Non-Verbal Gesturescited by 4
  32. 2025A survey of diversity quantification in natural language processing: The why, what, where and howcited by 4
  33. 2023Learning the Effects of Physical Actions in a Multi-modal Environmentcited by 3
  34. 2023SituatedGen: Incorporating Geographical and Temporal Contexts into Generative Commonsense Reasoningcited by 3
  35. 2025Evaluation of Cultural Competence of Vision-Language Modelscited by 3
  36. 2025World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Modelscited by 3
  37. 2022Are Akpans Trick or Treat: Unveiling Helpful Biases in Assistant Systemscited by 1
  38. 2025Toward Socially Aware Vision-Language Models: Evaluating Cultural Competence Through Multimodal Story Generationcited by 1

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