Summary of Culturebank: An Online Community-driven Knowledge Base Towards Culturally Aware Language Technologies, by Weiyan Shi et al.
CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language Technologies
by Weiyan Shi, Ryan Li, Yutong Zhang, Caleb Ziems, Chunhua yu, Raya Horesh, Rogério Abreu de Paula, Diyi Yang
First submitted to arxiv on: 23 Apr 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a novel pipeline for constructing cultural knowledge bases from online communities, aiming to enhance language models’ cultural awareness. The proposed CultureBank knowledge base is 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 for flexible interpretation and contextualized cultural scenarios for grounded evaluation. The authors evaluate different language models’ cultural awareness using CultureBank, identifying areas for improvement. They also fine-tune a language model on CultureBank, achieving better performances in zero-shot settings for two downstream cultural tasks. Finally, the paper offers recommendations for future culturally aware language technologies. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research creates a massive database of cultural knowledge to help computers understand different cultures better. The team collected information from online communities like TikTok and Reddit to build this database, which contains many examples of how people think about culture. Unlike other databases that might only show one way to think about culture, this one shows different perspectives too. The researchers tested how well some computer models could learn from this database and found areas where they need to improve. They also showed that by training a model on this database, it can do better at understanding cultural tasks without needing extra information. Overall, the goal is to make computers more aware of cultures so they can be used in ways that are more respectful and inclusive. |
Keywords
» Artificial intelligence » Knowledge base » Language model » Zero shot
