14 papers
Investigating Social Bias in Narrative Image Generation
Junyeong Park, Sowon Min, Euna Jang +5
Text-to-image (T2I) generation models are increasingly embedded in applications such as media content creation and education, raising concerns about how their outputs may reproduce…
Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability
Alicia Parrish, Rajat Shinde, Sanket Badhe +57
Current AI safety evaluation and benchmarking frameworks predominantly rely on Western-centric culture-agnostic defaults that mask critical regional laws, socio-linguistic nuances,…
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…
SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures
Nedjma Ousidhoum, Junho Myung, Carla Perez-Almendros +27
We present our shared task on evaluating the adaptability of LLMs and NLP systems across multiple languages and cultures. The task data consist of an extended version of our manual…
Open Korean Historical Corpus: A Millennia-Scale Diachronic Collection of Public Domain Texts
Seyoung Song, Nawon Kim, Songeun Chae +5
The history of the Korean language is characterized by a discrepancy between its spoken and written forms and a pivotal shift from Chinese characters to the Hangul alphabet. Howeve…
FINEST: Improving LLM Responses to Sensitive Topics Through Fine-Grained Evaluation
Juhyun Oh, Nayeon Lee, Chani Jung +5
Large Language Models (LLMs) often generate overly cautious and vague responses on sensitive topics, sacrificing helpfulness for safety. Existing evaluation frameworks lack systema…