P3B3: A Multi-Turn Conversational Benchmark for Measuring European and Brazilian Portuguese Variety Bias in LLMs
arXiv:2606.16753v1 Announce Type: new Abstract: As Large Language Models (LLMs) become embedded in everyday communication, capturing regional linguistic variation is essential for reliable and equitable language use. In Portuguese, European (pt-PT) and Brazilian (pt-BR) varieties remain unevenly represented, with pt-BR dominating in data quantity, while LLM preference for Portuguese variants remains underexplored. To address this gap, we introduce P3B3, an expert-curated language variety agnostic benchmark of conversational prompts, along with an evaluation framework for measuring variety bias
As LLMs become increasingly integrated into daily communication, the need for equitable and reliable language use across regional linguistic varieties is becoming critical.
This development highlights the growing recognition and effort to address linguistic biases in foundational AI models, which is crucial for their global adoption and equitable application.
The introduction of P3B3 provides a dedicated benchmark for evaluating and mitigating European and Brazilian Portuguese variety bias in LLMs, shifting the focus towards more culturally nuanced AI development.
- · Portuguese-speaking communities
- · Multilingual AI developers
- · Ethical AI researchers
- · Developers targeting non-English markets
- · LLM providers with unaddressed linguistic biases
- · Generative AI models limited to dominant dialects
- · Monolingual datasets for model training
P3B3 will enable LLM developers to measure and improve variety bias in Portuguese language models.
Improved representation of Portuguese varieties could lead to higher user satisfaction and broader market penetration for LLMs in Portuguese-speaking regions.
This initiative could spur the creation of similar variety-specific benchmarks for other languages, accelerating the development of truly global and inclusive AI.
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Read at arXiv cs.CL