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in-context learning is temporary. Training models to perform in-context learning can be viewed as a form of meta-learning, or "learning to learn".

Prompting to estimate model sensitivity

Research consistently demonstrates that LLMs are highly sensitive to subtle variations in prompt formatting, structure, and linguistic properties. Some studies have shown up to 76 accuracy points across formatting changes in few-shot settings. Linguistic features significantly influence

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