A BLEU score evaluates machine translation by comparing generated text with one or more high-quality reference translations. Unlike next-token accuracy, it accommodates slightly misaligned sequences and better reflects inference, where the decoder generates the target sentence from scratch. section 15.2.2
BLEU is useful because it:
- Compares machine-translated text with reference translations. section 15.2.2
- Tolerates wording whose sequence is slightly misaligned. section 15.2.2
- Addresses the limitations of validation accuracy for autoregressive translation. section 15.2.2
Translation evaluation
A model might generate “te lo voy mañana a decir” for “I will tell you tomorrow,” while a reference uses a different word order. BLEU is designed to assess similarity without requiring exact token-by-token agreement. section 15.2.2



