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Which is effective for adapting a large language model to each country's cultural preferences while keeping computational cost and memory usage low?
①Give many examples in-context each time.
②Relies on zero-shot generalization.
③Break down reasoning using chain-of-thought.
④Parameter-efficient fine-tuning such as adapters and LoRA
⑤Simply perform data augmentation.