Current cultural evaluations for large language models (LLMs) often reduce culture to single-turn factual recall via MCQs, failing to capture a common use case: users seeking practical help over multiple turns in culturally grounded scenarios. We introduce CultureConverse, a scalable, multilingual simulation and evalua...
Bryan Chen Zhengyu Tan, Wei-Hua Zheng, Thong T. Doan et al.· 0 citations
Overall, corpus growth increasingly favors global candidate ranking: lexical retrieval is the strongest scalable default, while agentic reasoning works best after ranked discovery rather than in place of it.
Pengyu Wang, Benfeng Xu, Shaohan Wang et al.· arXiv.org· 1 citation
CultureConverse is introduced, a scalable, multilingual simulation and evaluation harness for culturally grounded assistant dialogue that covers 10 East and Southeast Asian regions, 58 subgroup identities, and 7 domains and performance gains from fine-tuning on 27,860 high-quality CultureConverse-DS samples improve in-...
Bryan Chen Zhengyu Tan, Weihua Zheng, Thong T. Doan et al.· 0 citations
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