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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.
Fine-tuning LALMs on just the right layers, guided by layer-wise analysis, unlocks better paralinguistic understanding than naively fine-tuning everything.
