Hire Your Anthropologist! Rethinking Culture Benchmarks Through an Anthropological Lens
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Abstract (arXiv)
Cultural evaluation of large language models has become increasingly important, yet current benchmarks often reduce culture to static facts or homogeneous values. This view conflicts with anthropological accounts that emphasize culture as dynamic, historically situated, and enacted in practice. To analyze this gap, we introduce a four-part framework that categorizes how benchmarks frame culture, such as knowledge, preference, performance, or bias. Using this lens, we qualitatively examine 20 cultural benchmarks and identify six recurring methodological issues, including treating countries as cultures, overlooking within-culture diversity, and relying on oversimplified survey formats. Drawing on established anthropological methods, we propose concrete improvements: incorporating real-world narratives and scenarios, involving cultural communities in design and validation, and evaluating models in context rather than isolation. Our aim is to guide the development of cultural benchmarks that go beyond static recall tasks and more accurately capture the responses of the models to complex cultural situations.
Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 37 of its 85 references that are in the map. First posted on arXiv 7 Oct 2025.
Builds on
37 of 85 references.
References · 37
- 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 951
- 2020CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Modelscited by 703
- 2021BBQ: A Hand-Built Bias Benchmark for Question Answeringcited by 683
- 2021BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generationcited by 410
- 2019Social Bias Frames: Reasoning about Social and Power Implications of Languagecited by 377
- 2020Social Chemistry 101: Learning to Reason about Social and Moral Normscited by 253
- 2022Challenges and Strategies in Cross-Cultural NLPcited by 216
- 2024BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languagescited by 171
- 2024Towards Measuring and Modeling "Culture" in LLMs: A Surveycited by 166
- 2024Investigating Cultural Alignment of Large Language Modelscited by 140
- 2024The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Modelscited by 136
- 2020Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequencescited by 133
25 more
- 2021COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretrainingcited by 126
- 2024CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmarkcited by 118
- 2020X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Modelscited by 117
- 2024Survey of Cultural Awareness in Language Models: Text and Beyondcited by 101
- 2024Benchmarking Vision Language Models for Cultural Understandingcited by 100
- 2023When the Majority is Wrong: Modeling Annotator Disagreement for Subjective Taskscited by 89
- 2024Massively Multi-Cultural Knowledge Acquisition & LM Benchmarkingcited by 63
- 2024Evaluating Cultural and Social Awareness of LLM Web Agentscited by 43
- 2024SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languagescited by 41
- 2025Culture is Not Trivia: Sociocultural Theory for Cultural NLPcited by 40
- 2024WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisinescited by 39
- 2025Actions Speak Louder than Words: Agent Decisions Reveal Implicit Biases in Language Modelscited by 30
- 2024M5 -- A Diverse Benchmark to Assess the Performance of Large Multimodal Models Across Multilingual and Multicultural Vision-Language Taskscited by 27
- 2024LLM-GLOBE: A Benchmark Evaluating the Cultural Values Embedded in LLM Outputcited by 27
- 2023Large Language Models are Built-in Autoregressive Search Enginescited by 26
- 2023CDEval: A Benchmark for Measuring the Cultural Dimensions of Large Language Modelscited by 23
- 2024Pedagogical Alignment of Large Language Modelscited by 19
- 2024MBIAS: Mitigating Bias in Large Language Models While Retaining Contextcited by 15
- 2025SeaExam and SeaBench: Benchmarking LLMs with Local Multilingual Questions in Southeast Asiacited by 13
- 2025Humanizing Machines: Rethinking LLM Anthropomorphism Through a Multi-Level Framework of Designcited by 11
- 2025Embracing Contradiction: Theoretical Inconsistency Will Not Impede the Road of Building Responsible AI Systemscited by 8
- 2024Social Norms in Cinema: A Cross-Cultural Analysis of Shame, Pride and Prejudicecited by 6
- 2024CASA: Causality-driven Argument Sufficiency Assessmentcited by 4
- 2024MACT: Model-Agnostic Cross-Lingual Training for Discourse Representation Structure Parsingcited by 3
- 2025Rethinking AI Cultural Alignmentcited by 3
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Citing papers per year: 2025: 1; 2026: 12.
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- 2026Towards Valid Student Simulation with Large Language Modelscited by 7
- 2025VideoNorms: Benchmarking Cultural Awareness of Video Language Modelscited by 4
- 2026Sentipolis: Emotion-Aware Agents for Social Simulationscited by 2
- 2026The Culture Funnel: You Can't Align What isn't in the Datacited by 2
- 2026Kinship Data Benchmark for Multi-hop Reasoningcited by 1
- 2026The Algorithmic Gaze of Image Quality Assessment: An Audit and Trace Ethnography of the LAION-Aesthetics Predictorcited by 1
- 2026Toward Culturally Grounded Natural Language Processingcited by 0
- 2026SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Culturescited by 0
- 2026Quantifying the Salience of Geo-Cultural Values for Pluralistic Safety Alignmentcited by 0
- 2026SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understandingcited by 0
- 2026When Trivia Is Not Trivial: Everyday Knowledge Failures in Multilingual LLMscited by 0
- 2026Beyond Cultural Knowledge: Evaluating Arabic Cultural Appropriateness of Large Language Modelscited by 0
1 more
- 2026Supporting and Performing Culture from the Insidecited by 0
- 2026Supporting and Performing Culture from the Inside26 Sep 2026
- 2026Beyond Cultural Knowledge: Evaluating Arabic Cultural Appropriateness of Large Language Models30 Jul 2026
- 2026When Trivia Is Not Trivial: Everyday Knowledge Failures in Multilingual LLMs23 Jul 2026
- 2026The Culture Funnel: You Can't Align What isn't in the Data11 Jun 2026
- 2026SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understanding2 Jun 2026
- 2026Quantifying the Salience of Geo-Cultural Values for Pluralistic Safety Alignment29 May 2026
- 2026SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures4 May 2026
- 2026Toward Culturally Grounded Natural Language Processing27 Mar 2026
- 2026Sentipolis: Emotion-Aware Agents for Social Simulations25 Jan 2026
- 2026The Algorithmic Gaze of Image Quality Assessment: An Audit and Trace Ethnography of the LAION-Aesthetics Predictor14 Jan 2026
- 2026Kinship Data Benchmark for Multi-hop Reasoning12 Jan 2026
- 2026Towards Valid Student Simulation with Large Language Models9 Jan 2026
1 more
- 2026Sentipolis: Emotion-Aware Agents for Social Simulationscited by 2
- 2026Sentipolis: Emotion-Aware Agents for Social Simulations25 Jan 2026
- 2026Kinship Data Benchmark for Multi-hop Reasoningcited by 1
- 2026Kinship Data Benchmark for Multi-hop Reasoning12 Jan 2026
- 2026Towards Valid Student Simulation with Large Language Modelscited by 7
- 2025VideoNorms: Benchmarking Cultural Awareness of Video Language Modelscited by 4
- 2026The Culture Funnel: You Can't Align What isn't in the Datacited by 2
- 2026The Algorithmic Gaze of Image Quality Assessment: An Audit and Trace Ethnography of the LAION-Aesthetics Predictorcited by 1
- 2026Toward Culturally Grounded Natural Language Processingcited by 0
- 2026SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Culturescited by 0
- 2026SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understandingcited by 0
- 2026When Trivia Is Not Trivial: Everyday Knowledge Failures in Multilingual LLMscited by 0
- 2026Beyond Cultural Knowledge: Evaluating Arabic Cultural Appropriateness of Large Language Modelscited by 0
- 2026Supporting and Performing Culture from the Insidecited by 0
- 2026Supporting and Performing Culture from the Inside26 Sep 2026
- 2026Beyond Cultural Knowledge: Evaluating Arabic Cultural Appropriateness of Large Language Models30 Jul 2026
- 2026When Trivia Is Not Trivial: Everyday Knowledge Failures in Multilingual LLMs23 Jul 2026
- 2026The Culture Funnel: You Can't Align What isn't in the Data11 Jun 2026
- 2026SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understanding2 Jun 2026
- 2026SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures4 May 2026
- 2026Toward Culturally Grounded Natural Language Processing27 Mar 2026
- 2026The Algorithmic Gaze of Image Quality Assessment: An Audit and Trace Ethnography of the LAION-Aesthetics Predictor14 Jan 2026
- 2026Towards Valid Student Simulation with Large Language Models9 Jan 2026
- 2025VideoNorms: Benchmarking Cultural Awareness of Video Language Models9 Oct 2025
Similar, not cited
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- 2025Randomness, Not Representation: The Unreliability of Evaluating Cultural Alignment in LLMs
- 2026Carefully Considering Culture: Analyzing LLM Alignment in Single- and Multi-Cultural Settings using Cultural Consensus Theory
- 2025WorldView-Bench: A Benchmark for Evaluating Global Cultural Perspectives in Large Language Models
- 2025Culture is Everywhere: A Call for Intentionally Cultural Evaluation
- 2026Aligned but Flattened: Analyzing the Trade-off between Cultural Alignment and Diversity in LLMs
- 2025CURE: Cultural Understanding and Reasoning Evaluation - A Framework for "Thick" Culture Alignment Evaluation in LLMs
- 2025CCD-Bench: Probing Cultural Conflict in Large Language Model Decision-Making
- 2025Break the Checkbox: Challenging Closed-Style Evaluations of Cultural Alignment in LLMs