CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language Technologies
<|reference_start|>CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language Technologies: 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 .<|reference_end|>
@article{shi2024culturebank:,
    title={CultureBank: An Online Community-Driven Knowledge Base Towards
  Culturally Aware Language Technologies},
    author={Weiyan Shi, Ryan Li, Yutong Zhang, Caleb Ziems, Chunhua yu, Raya
  Horesh, Rog'erio Abreu de Paula, Diyi Yang},
    journal={arXiv preprint arXiv:2404.15238},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.15238},
    primaryClass={cs.CL cs.AI}
}