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CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language Technologies
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To enhance language models' cultural awareness, we design a generalizable pipeline to construct cultural knowledge bases from different online communities on a massive scale. With the pipeline, we construct CultureBank, a knowledge base built upon users' self-narratives with 12K cultural descriptors sourced from TikTok and 11K from Reddit. Unlike previous cultural knowledge resources, CultureBank contains diverse views on cultural descriptors to allow flexible interpretation of cultural knowledge, and contextualized cultural scenarios to help grounded evaluation. With CultureBank, we evaluate different LLMs' cultural awareness, and identify areas for improvement. We also fine-tune a language model on CultureBank: experiments show that it achieves better performances on two downstream cultural tasks in a zero-shot setting. Finally, we offer recommendations based on our findings for future culturally aware language technologies. The project page is https://culturebank.github.io . The code and model is at https://github.com/SALT-NLP/CultureBank . The released CultureBank dataset is at https://huggingface.co/datasets/SALT-NLP/CultureBank .
Forward citations
Cited by 9 Pith papers
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Cross-Lingual Transfer of Cultural Knowledge: An Asymmetric Phenomenon
Cross-lingual transfer of cultural knowledge is bidirectional for high-resource languages and asymmetric for low-resource ones, with corpus frequency correlating with transfer success.
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CultureSynth: A Hierarchical Taxonomy-Guided and Retrieval-Augmented Framework for Cultural Question-Answer Synthesis
A taxonomy-guided retrieval-augmented framework generates CultureSynth-7, a multilingual cultural QA benchmark, and its evaluation of 14 LLMs suggests cultural competence emerges around 3B parameters.
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CulFiT: A Fine-grained Cultural-aware LLM Training Paradigm via Multilingual Critique Data Synthesis
A multilingual critique-data training paradigm with a knowledge-unit reward improves LLM cultural alignment on several benchmarks, but its headline benchmark is evaluated with the same LLM-judged metric used to select...
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When One LLM Drools, Multi-LLM Collaboration Rules
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On The Origin of Cultural Biases in Language Models: From Pre-training Data to Linguistic Phenomena
Arab cultural entities that double as everyday Arabic words are harder for language models to recognize, especially when tokenized as single tokens.
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CultureVLM: Characterizing and Improving Cultural Understanding of Vision-Language Models for over 100 Countries
CultureVerse is a 188-country, 19k-concept visual QA benchmark, and fine-tuning open VLMs on it improves cultural accuracy, but the main evaluation shares concepts between training and test sets.
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Against 'softmaxing' culture
A position paper arguing that AI evaluations should shift from defining culture to understanding when culture becomes relationally valid.
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