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LLM ensembles excel at classifying narrative similarity, but simpler embedding models can achieve comparable performance with clever pre- and post-processing.
Injecting XML annotation tags directly into machine translation surprisingly boosts both translation quality and cross-lingual transfer performance, achieving up to +39.9 F1 on NER.
