Challenge: Using large vision-language models to understand cultural contexts is a critical area of research.
Approach: They conduct a thorough evaluation of multimodal models at different scales, focusing on their alignment with cultural values.
Outcome: The proposed models show that they exhibit sensitivity to cultural values but their performance is highly context-dependent.

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Challenge: Prior research has revealed that certain abstract concepts are linearly represented as directions in the representation space of LLMs, predominantly centered around English.
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The Potential and Challenges of Evaluating Attitudes, Opinions, and Values in Large Language Models (2024.findings-emnlp)

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Challenge: Recent advances in Large Language Models have sparked interest in validating human-like cognitive-behavioral traits.
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From Surveys to Narratives: Rethinking Cultural Value Adaptation in LLMs (2025.emnlp-main)

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Challenge: Adapting cultural values in Large Language Models presents significant challenges due to biases and data limitations.
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Navigating the Cultural Kaleidoscope: A Hitchhiker’s Guide to Sensitivity in Large Language Models (2025.naacl-long)

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Challenge: Cultural harm arises when LLMs misrepresent or normalize values, identities, and practices in ways that conflict with the norms of diverse cultural groups.
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Bias in the Ear of the Listener: Assessing Sensitivity in Audio Language Models Across Linguistic, Demographic, and Positional Variations (2026.findings-eacl)

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Challenge: Recent advances extend language understanding beyond text to speech, enabling unified reasoning across modalities.
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Global Gallery: The Fine Art of Painting Culture Portraits through Multilingual Instruction Tuning (2024.naacl-long)

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Challenge: This study examines the ability of Large Language Models to encapsulate cultural nuances across diverse linguistic landscapes.
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Do LLMs Align Human Values Regarding Social Biases? Judging and Explaining Social Biases with LLMs (2025.findings-emnlp)

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Challenge: Large language models can lead to undesired consequences when misaligned with human values . previous studies have shown misalignment of LLMs with human value using expert-designed or agent-based emulated bias scenarios .
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Towards Better Value Principles for Large Language Model Alignment: A Systematic Evaluation and Enhancement (2025.acl-long)

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Challenge: Large Language Models (LLMs) show remarkable performance across tasks . alignment with human values is critical for their responsible development.
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MMAC: A Multilingual, Multimodal Alignment Framework for Cultural Grounding Evaluation (2026.acl-long)

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Challenge: Existing models lack cultural alignment across modalities and languages . a new framework to assess cultural awareness across linguistics and languages is needed .
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ALIGN: Word Association Learning for Cultural Alignment in Large Language Models (2026.acl-long)

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Challenge: Large language models exhibit cultural bias from over-represented viewpoints in training data, yet cultural alignment remains a challenge due to limited cultural knowledge and a lack of exploration into effective learning approaches.
Approach: They propose a cost-efficient method for fine-tuning large language models on native speakers’ word-association norms and a preference optimization method to improve cultural alignment.
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