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20242026
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cs.CL2026

JuICE: A Benchmark for Evaluating LLM-Judge in Identifying Cultural Errors

Jiho Jin, Junho Myung, Juhyun Oh +5

As large language models (LLMs) are increasingly deployed to users around the world, they are integrated into everyday tasks across diverse cultural contexts, from drafting persona…

cs.CL2026

Cultural Authenticity: Comparing LLM Cultural Representations to Native Human Expectations

Erin MacMurray van Liemt, Aida Davani, Sinchana Kumbale +2

Cultural representation in Large Language Model (LLM) outputs has primarily been evaluated through the proxies of cultural diversity and factual accuracy. However, a crucial gap re…

cs.CL2026

SAFARI: A Community-Engaged Approach and Dataset of Stereotype Resources in the Sub-Saharan African Context

Aishwarya Verma, Laud Ammah, Olivia Nercy Ndlovu Lucas +3

Stereotype repositories are critical to assess generative AI model safety, but currently lack adequate global coverage. It is imperative to prioritize targeted expansion, strategic…

cs.CL2025

Towards Geo-Culturally Grounded LLM Generations

Piyawat Lertvittayakumjorn, David Kinney, Vinodkumar Prabhakaran +2

Generative large language models (LLMs) have demonstrated gaps in diverse cultural awareness across the globe. We investigate the effect of retrieval augmented generation and searc…

cs.CL2024

Assessing biomedical knowledge robustness in large language models by query-efficient sampling attacks

R. Patrick Xian, Alex J. Lee, Satvik Lolla +4

The increasing depth of parametric domain knowledge in large language models (LLMs) is fueling their rapid deployment in real-world applications. Understanding model vulnerabilitie…