Also known as: BLEURT (Bilingual Evaluation Understudy From Transformers) Β· BLEURT Β· Bilingual Evaluation Understudy From Transformers
Bilingual Evaluation Understudy From Transformers (BLEURT) is a learned evaluation metric for text generation and machine translation. It uses a BERT-based model fine-tuned on human judgments to assess semantic similarity and output quality. Compared with traditional BLEU, BLEURT can better account for meaning-preserving paraphrases.
A metric for evaluating machine translations from one language to another, particularly to and from English. For translations to and from English, BLEURT aligns more closely to human ratings than BLEU. Unlike BLEU, BLEURT emphasizes semantic (meaning) similarities and can accommodate paraphrasing. BLEURT relies on a pre-trained large language model (BERT to be exact) that is then fine-tuned on text from human translators. The original paper on this metric is BLEURT: Learning Robust Metrics for Text Generation.