Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability
Current AI safety evaluation and benchmarking frameworks predominantly rely on Western-centric culture-agnostic defaults that mask critical regional laws, socio-linguistic nuances, and cultural taboos, leaving Vision-Language Models (VLMs) vulnerable in global deployments. We introduce Pluralis v0.1: a novel multimodal, multi-regional, and multilingual dataset built from a culture-first perspective. Spanning 6,448 prompts across six Asia-Pacific countries (Bangladesh, India, Korea, Pakistan, Singapore, Taiwan) and eight languages, Pluralis diverges from prior work by natively sourcing localize
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- PossiblePossibly related (embedding) · 53%Nemotron 3.5 Content Safety: Customizable Multimodal Safety for Global Enterprise AI →
- PossiblePossibly related (embedding) · 53%PacificAI/langtest →
- PossiblePossibly related (embedding) · 50%Asian AI startups launch Mythos-like models as Anthropic’s export ban drags on →
- PossiblePossibly related (embedding) · 50%After spooking Trump into safety testing, Anthropic AI models get global release →
- PossiblePossibly related (embedding) · 47%Global push for AI governance amid warnings of ‘catastrophic harm’ - UN News →
- LinkedLinked via arxiv author · 85%Alicia Parrish →
“Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability”
- LinkedLinked via arxiv author · 85%Rajat Shinde →
“Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability”
- LinkedLinked via arxiv author · 85%Sanket Badhe →
“Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability”