arXiv AI
Jun 8

The Masked Advantage: Uncovering Local-Language Access to Cultural Knowledge in LLMs

arXiv:2606. 07422v1 Announce Type: cross Abstract: Large language models are increasingly used to answer culturally grounded questions across languages, yet it remains unclear whether local cultural knowledge is better accessed through English or the local language.

By Yang Zhang, Xiao Fei, Amr Mohamed, Sarah Almeida Carneiro, Mersin Konomi, Mingmeng Geng, Ahmed Asaad, Guokan Shang, Michalis Vazirgiannis
arXiv Computation and Language
Oct 21

The Culture Within: Towards Mechanistic Understanding of Cultural Reasoning in LLMs

The paper introduces CultureLens, a benchmark with 9,261 scenarios from 75 countries that tests how large language models (LLMs) incorporate cultural information. Experiments on Llama‑3.1‑8B, Gemma‑3‑12B, and Qwen‑3.5‑27B show that presenting a contradictory cultural norm reduces aligned answers by 32‑47 percentage points, even when the model knows the correct country. Fine‑tuning with contradictory‑norm examples improves alignment to 85‑93% under contradictory norms while only slightly affecting performance under true norms.

By Samee Arif, Furkan Danisman, Angana Borah, Honglak Lee, Dehan Kong, Lajanugen Logeswaran, Moontae Lee, Zhijing Jin, Rada Mihalcea
arXiv AI
Oct 5

CuBEs: Culturally-Situated Behavioral Evaluations and the Limitations of Culture-Blind LLM Judges

CuBEs introduces culturally‑situated behavioral evaluations for large language models, adding cultural context to test scenarios and assessments. The authors built a human‑labeled dataset covering 12 cultures, revealing significant cross‑cultural differences that one‑size‑fits‑all judgments miss. Evaluating 13 LLMs shows that culturally situated tests uncover varied behaviors, such as Western political bias versus non‑Western religious or colonial biases, which standard evaluations overlook.

By Hoda Ayad, Tanu Mitra, Abhishek Mukherji
arXiv Computation and Language
Oct 19

Cultural (In)Competence: Investigating Culture-Specific Stereotype Detection Capabilities of LLMs

arXiv:2610.22545v1 Announce Type: new Abstract: Stereotypes are subjective constructs that are mediated by the cultural context in which they are viewed. Successfully modeling them thus also requires...

By Maximilian Splieth\"over, Jannes L\"otfering, Dominik Bachmann, Alexander Espig, Willem Zuidema, Katrin Schulz, Henning Wachsmuth