{
 "id": "Incomple/SubgroupValuesSG-outputs",
 "owner": "Incomple",
 "name": "SubgroupValuesSG-outputs",
 "downloads": 1128,
 "likes": 0,
 "last_modified": "2026-10-15T23:07:22.000Z",
 "stated_licence": "cc-by-nc-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [],
 "citation": "@inproceedings{tanCanPersonaPromptedLLMs2026,\n  title = {Can {{Persona-Prompted LLMs Emulate Subgroup Values}}? {{An Empirical Analysis}} of {{Generalisability}} and {{Fairness}} in {{Cultural Alignment}}},\n  shorttitle = {Can {{Persona-Prompted LLMs Emulate Subgroup Values}}?},\n  booktitle = {Proceedings of the 64th {{Annual Meeting}} of the {{Association}} for {{Computational Linguistics}} ({{Volume}} 1: {{Long Papers}})},\n  author = {Tan, Bryan Chen Zhengyu and Liu, Zhengyuan and Yi, Xiaoyuan and Yao, Jing and Xie, Xing and Chen, Nancy F. and Lee, Roy Ka-Wei},\n  editor = {Liakata, Maria and Moreira, Viviane P. and Zhang, Jiajun and Jurgens, David},\n  year = 2026,\n  month = jul,\n  pages = {24571--24590},\n  publisher = {Association for Computational Linguistics},\n  address = {San Diego, California, United States},\n  doi = {10.18653/v1/2026.acl-long.1127},\n  urldate = {2026-09-14},\n  abstract = {Despite their global prevalence, many Large Language Models (LLMs) are aligned to a monolithic, often Western-centric set of values. This paper investigates the more challenging task of fine-grained value alignment: examining whether LLMs can emulate the distinct cultural values of demographic subgroups. Using Singapore as a case study and the World Values Survey (WVS), we examine the value landscape and show that even state-of-the-art models like GPT-4.1 achieve only 57.4\\% accuracy in predicting subgroup modal preferences. We construct a dataset of over 20,000 samples to train and e",
 "signal": "restrictive",
 "reason": "The declared licence (cc-by-nc-4.0) is classified as having use restrictions.",
 "revision": "3ca150b7376791377986b318d71a1603495798af",
 "stated_evidence": "https://huggingface.co/datasets/Incomple/SubgroupValuesSG-outputs/blob/3ca150b7376791377986b318d71a1603495798af/README.md",
 "file_evidence": "https://huggingface.co/datasets/Incomple/SubgroupValuesSG-outputs/tree/3ca150b7376791377986b318d71a1603495798af",
 "card_nc": false
}