This research evaluates how different data filtering methods impact LLM-based machine translation performance specifically for biomedical content between English and Polish.

• Addresses computational challenges of training LLMs on massive bilingual datasets
• Compares effectiveness of various filtering techniques for reducing dataset size while maintaining quality
• Provides domain-specific insights for biomedical translation requirements
• Offers practical guidance on optimizing translation models for specialized medical content

Why it matters: Accurate medical translation is crucial for global healthcare information exchange, and this research helps identify the most efficient approaches to build specialized translation systems while reducing computational costs.

A comparison of data filtering techniques for English-Polish LLM-based machine translation in the biomedical domain