Learned classifiers for selecting optimal prompting strategies in multilingual LLMs outperform fixed approaches, generalize to new tasks, and show benefits driven primarily by language resource levels rather than translation quality.
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No One Fits All: From Fixed Prompting to Learned Routing in Multilingual LLMs
Learned classifiers for selecting optimal prompting strategies in multilingual LLMs outperform fixed approaches, generalize to new tasks, and show benefits driven primarily by language resource levels rather than translation quality.