mlsanityData to 14 Oct 2026

Tanawpamana: Benchmarking Vision-Language Models on Philippine Cultural Heritage Sites

arXiv 2610.17596 ↗First posted 13 Oct 2026cs.CV cs.AI cs.CLcited by 0

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Abstract (arXiv)

Vision-language models are increasingly used to identify and describe places, yet their recognition and knowledge of specific cultures remain poorly understood, particularly in underrepresented regions such as the Philippines. This study introduces the Tanawpamana Dataset, a repository of Philippine heritage site images with metadata based on the Talapamana registry of the National Commission for Culture and the Arts of the Philippines. We also introduce the Tanawpamana Benchmark, comprising 4,046 tasks designed to evaluate models' recognition and knowledge of heritage sites. Evaluating seven vision-language models, we find that they struggle more with fine-grained visual discrimination among similar heritage sites than with coarse recognition, and that their geographic knowledge is weaker when inferred from image inputs than from text.

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References · 13

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1 more
  1. 2025Rice-VL: Evaluating Vision-Language Models for Cultural Understanding Across ASEAN Countriescited by 2

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  1. 2026ChinaHeritaQA: A Culturally-Grounded Visual Question Answering Dataset for World Heritage Sites in China
  2. 2026Appear2Meaning: A Cross-Cultural Benchmark for Structured Cultural Metadata Inference from Images
  3. 2026AmalthAI: An Open-Source Computer Vision Platform for Cultural Heritage
  4. 2024Understanding Museum Exhibits using Vision-Language Reasoning
  5. 2026On the Cultural Anachronism and Temporal Reasoning in Vision Language Models
  6. 2024Crossroads of Continents: Automated Artifact Extraction for Cultural Adaptation with Large Multimodal Models
  7. 2024An archaeological Catalog Collection Method Based on Large Vision-Language Models
  8. 2024From Local Concepts to Universals: Evaluating the Multicultural Understanding of Vision-Language Models