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Fine-tuning VLMs for regional relevance doesn't have to sacrifice global performance: a simple data filtering and model merging technique boosts cultural relevance by 5-15% while barely impacting overall accuracy.
Forget expensive fine-tuning: linguistically-informed prompting offers a lightweight, but sometimes unreliable, path to low-resource translation with LLMs.