Insufficiency of Prompting for Tasks Outside an LLM's Pre-training Scope

Diagnosing In-Context Learning Failure

A research team is using a powerful, general-purpose language model for a highly specialized task: translating ancient, obscure texts. The team has invested significant effort in creating detailed prompts with multiple high-quality examples of translations. Despite this, the model's outputs are consistently nonsensical. Which of the following statements provides the most accurate evaluation of this situation?

A sufficiently well-engineered prompt, complete with numerous high-quality examples, can overcome the limitations of a language model's pre-training data to successfully perform any new task.