Psychologically-informed chain-of-thought prompts for metaphor understanding in large language models

Understand

Probabilistic models of language understanding are valuable tools for investigating human language use.

• However, they need to be hand-designed for a particular domain.
• In contrast, large language models (LLMs) are trained on text that spans a wide array of domains, but they lack the structure and interpretability of probabilistic models.
• In this paper, we use chain-of-thought prompts to introduce structures from probabilistic models into LLMs.