LLMs handle idioms and metaphors by recognizing them as patterns learned during training. When exposed to phrases like "kick the bucket" or "a piece of cake," they associate these expressions with their intended meanings based on the context in which they appear in the training data. For example, an LLM can interpret "kick the bucket" as "to die" if the surrounding context supports this meaning.
However, their understanding is limited to the data they have been trained on. If an idiom or metaphor is uncommon or specific to a niche cultural context, the LLM might misinterpret it or generate a literal response. For instance, it might struggle with newer or highly localized idiomatic expressions.
Developers can improve an LLM's handling of idioms and metaphors by fine-tuning it with culturally rich or domain-specific datasets. Despite this, LLMs lack true comprehension and rely on probability-based predictions, which means they may occasionally produce incorrect interpretations in ambiguous or novel scenarios.