Small open-source LLMs achieve competitive system-level correlations with human judgments in machine translation quality estimation, outperforming traditional neural metrics and fine-tuned models via single-pass multi-output prompting.
MQM - APE : Toward High-Quality Error Annotation Predictors with Automatic Post-Editing in LLM Translation Evaluators
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CompactQE: Interpretable Translation Quality Estimation via Small Open-Weight LLMs
Small open-source LLMs achieve competitive system-level correlations with human judgments in machine translation quality estimation, outperforming traditional neural metrics and fine-tuned models via single-pass multi-output prompting.