In the news
Large Language Models for Machine Translation Quality Annotation: Humans and Models Are Both Challenged
Apple Machine Learning Research · Published · 3 min read
In 30 seconds
- What happened
- Apple researchers evaluated large language models for machine translation quality annotation across 70 language pairs, finding both LLMs and humans struggle with reliability.
- Why it matters
- Machine translation teams considering LLMs to replace human evaluation should understand current limitations before deployment in production systems.
- Watch out
- LLMs exceed human agreement on some tasks but remain unreliable for most settings; they struggle with minor errors and language variants.
- llm
- language model
- eval
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