mqm

Introduces TQLite, a distillation framework that uses a multi-LRM jury to train small language models for real-time MQM-based translation quality evaluation, achieving performance far exceeding off-the-shelf SLMs while remaining cost-effective.

This paper demonstrates that small open-weight LLMs (<30B parameters) can achieve competitive interpretable translation quality estimation, including MQM error annotations and corrections, rivaling much larger proprietary models while preserving data privacy.