3 papers
cs.CL2026
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,…
cs.CR2026
TWGuard: A Case Study of LLM Safety Guardrails for Localized Linguistic Contexts
Hua-Rong Chu, Kuan-Chun Wang, Yao-Te Huang
Safety guardrails have become an active area of research in AI safety, aimed at ensuring the appropriate behavior of large language models (LLMs). However, existing research lacks…
q-bio.NC2023
Learning High-Order Relationships of Brain Regions
Weikang Qiu, Huangrui Chu, Selena Wang +4
Discovering reliable and informative relationships among brain regions from functional magnetic resonance imaging (fMRI) signals is essential in phenotypic predictions. Most of the…