Not All Personas Are Worth It: Culture-Reflective Persona Data Augmentation
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Abstract (arXiv)
Incorporating personas into conversational AI models is crucial for achieving authentic and engaging interactions. However, the cultural diversity and adaptability of existing persona datasets is often overlooked, reducing their efficacy in building culturally aware AI systems. To address this issue, we propose a two-step pipeline for generating culture-specific personas and introduce KoPersona, a dataset comprising 200,000 personas designed to capture Korean cultural values, behaviors, and social nuances. A comprehensive evaluation through various metrics validates the quality of KoPersona and its relevance to Korean culture. This work not only contributes to persona-based research, but also establishes a scalable approach for creating culturally relevant personas adaptable to various languages and cultural contexts.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 9 references that are in the map. First posted on arXiv 17 Mar 2025.
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References · 6
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,276
- 2018Personalizing Dialogue Agents: I have a dog, do you have pets too?cited by 828
- 2024Scaling Synthetic Data Creation with 1,000,000,000 Personascited by 417
- 2023Faithful Persona-based Conversational Dataset Generation with Large Language Modelscited by 47
- 2022Building a Role Specified Open-Domain Dialogue System Leveraging Large-Scale Language Modelscited by 26
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