CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language Technologies
This addresses the need for culturally aware language technologies by providing a resource for flexible interpretation and evaluation, though it is incremental as it builds on existing knowledge base methods.
The authors tackled the problem of enhancing language models' cultural awareness by constructing CultureBank, a large-scale knowledge base from online communities, which includes 23K cultural descriptors from TikTok and Reddit. They used it to evaluate LLMs, identify improvement areas, and fine-tune a model that achieved better zero-shot performance on cultural tasks.
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 .