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Monolingual models can achieve cross-lingual alignment without joint training, revealing the power of linguistic structure over shared parameters.
Multilingual LLM evaluators can misjudge content, favoring lower-resource languages and potentially allowing harmful material to slip through safety filters despite high accuracy scores.
Multilingual spoken dialogue systems still struggle with consistent performance across languages, even with high-resource languages, as shown by a new large-scale dataset.
