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
This study systematically dissects design choices along three dimensions: foundational components, perception essentials, and action modeling perspectives and distill 12 key findings that together form a practical recipe for building strong VLA models, resulting in a simple yet effective model, VLANeXt.
Xiao-Ming Wu, Kang Liao, Yi-Hang Luo et al.· 12 citations· ⚡3
The causes of modal divergence are probed, offering insights into fostering culturally robust MLLMs, and a Multilingual, Multimodal Alignment framework for Cultural grounding evaluation is proposed.
Weihua Zheng, Zhengyuan Liu, Tanmoy Chakraborty et al.· Annual Meeting of the Associ...· 0 citations
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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