mlsanityData to 14 Oct 2026

On the Cultural Anachronism and Temporal Reasoning in Vision Language Models

arXiv 2605.15071 ↗First posted 14 May 2026cs.CV cs.AI cs.CLcited by 0

On the map: LLM reasoning → Multimodal reasoning

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Abstract (arXiv)

Vision-Language Models (VLMs) are increasingly applied to cultural heritage materials, from digital archives to educational platforms. This work identifies a fundamental issue in how these models interpret historical artifacts. We define this phenomenon as cultural anachronism, the tendency to misinterpret historical objects using temporally inappropriate concepts, materials, or cultural frameworks. To quantify this phenomenon, we introduce the Temporal Anachronism Benchmark for Vision-Language Models (TAB-VLM), a dataset of 600 questions across six categories, designed to evaluate temporal reasoning on 1,600 Indian cultural artifacts spanning prehistoric to modern periods. Systematic evaluations of ten state-of-the-art models reveal significant deficiencies on our benchmark, and even the best model (GPT-5.2) achieves only 58.7% overall accuracy. The performance gap persists across varying architectures and scales, suggesting that cultural anachronism represents a significant limitation in visual AI systems, regardless of model size. These findings highlight the disparity between current VLM capabilities and the requirements for accurately interpreting cultural heritage materials, particularly for non-Western visual cultures underrepresented in training data. Our benchmark provides a foundation for enhancing temporal cognition in multimodal AI systems that interact with historical artifacts. The dataset and code are available in our project page.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Multimodal reasoning, one of 17 directions in LLM reasoning. Builds on 33 of its 52 references that are in the map. First posted on arXiv 14 May 2026.

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33 of 52 references.

Closest ancestors · 2

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  1. 2025Can Multimodal LLMs do Visual Temporal Understanding and Reasoning? The answer is No!18 Jan
  2. 2023Large Language Models are Temporal and Causal Reasoners for Video Question Answering24 Oct

Other references · 31

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  5. 2025InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Modelscited by 1,834
  6. 2022CoCa: Contrastive Captioners are Image-Text Foundation Modelscited by 1,274
  7. 2021Multimodal datasets: misogyny, pornography, and malignant stereotypescited by 327
  8. 2024Towards Measuring and Modeling "Culture" in LLMs: A Surveycited by 167
  9. 2022Holistic Evaluation of Language Modelscited by 131
  10. 2024Benchmarking Vision Language Models for Cultural Understandingcited by 101
  11. 2023Aligning Language Models to User Opinionscited by 99
  12. 2024Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoningcited by 88
19 more
  1. 2024Massively Multi-Cultural Knowledge Acquisition & LM Benchmarkingcited by 63
  2. 2024How Well Do LLMs Represent Values Across Cultures? Empirical Analysis of LLM Responses Based on Hofstede Cultural Dimensionscited by 52
  3. 2024NormAd: A Framework for Measuring the Cultural Adaptability of Large Language Modelscited by 48
  4. 2025A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challengescited by 47
  5. 2025CultureVLM: Characterizing and Improving Cultural Understanding of Vision-Language Models for over 100 Countriescited by 42
  6. 2023TRAM: Benchmarking Temporal Reasoning for Large Language Modelscited by 40
  7. 2023TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Modelscited by 39
  8. 2024Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language modelscited by 35
  9. 2023Are Multilingual LLMs Culturally-Diverse Reasoners? An Investigation into Multicultural Proverbs and Sayingscited by 32
  10. 2024Beyond Aesthetics: Cultural Competence in Text-to-Image Modelscited by 30
  11. 2024CulturalBench: A Robust, Diverse, and Challenging Cultural Benchmark by Human-AI CulturalTeamingcited by 30
  12. 2024CulturePark: Boosting Cross-cultural Understanding in Large Language Modelscited by 24
  13. 2024Timo: Towards Better Temporal Reasoning for Language Modelscited by 21
  14. 2025Time Blindness: Why Video-Language Models Can't See What Humans Can?cited by 18
  15. 2025Can Language Models Represent the Past without Anachronism?cited by 14
  16. 2025Time Travel: A Comprehensive Benchmark to Evaluate LMMs on Historical and Cultural Artifactscited by 11
  17. 2025TimeCausality: Evaluating the Causal Ability in Time Dimension for Vision Language Modelscited by 9
  18. 2024DateLogicQA: Benchmarking Temporal Biases in Large Language Modelscited by 2
  19. 2024Explainable Search and Discovery of Visual Cultural Heritage Collections with Multimodal Large Language Modelscited by 1

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