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Standard MCQA metrics can mislead evaluations by over 2 points due to phrasing sensitivity, but ParaEval cuts this gap to under 1 point, revealing true model capabilities.
Forget scaling laws: a specialized 8B parameter translation model can outperform a 70B general-purpose LLM on 1,600 languages.
OmniSONAR halves cross-lingual search error on FLORES and reduces error by 15x on BIBLE, proving that truly universal sentence embeddings across thousands of languages and modalities are now within reach.
