CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language Technologies

Weiyan Shi, Ryan Li, Yutong Zhang, Caleb Ziems, Chunhua yu +3 more
4/23/2024
cs.CLcs.AI

Official code: SALT-NLP/CultureBank (50 stars, MIT, last commit 2025-09-29).

Abstract

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 .

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MIT
5010PythonApr 5, 20241 years agoMIT

Cite this paper

@article{shi2024culturebank,
  title  = {CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language Technologies},
  author = {Weiyan Shi and Ryan Li and Yutong Zhang and Caleb Ziems and Chunhua yu and Raya Horesh and Rogério Abreu de Paula and Diyi Yang},
  year   = {2024},
  eprint = {2404.15238},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.15238v1}
}

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