Large Language Model Displays Emergent Ability to Interpret Novel Literary Metaphors
Nicholas Ichien, Du\v{s}an Stamenkovi\'c, Keith J. Holyoak

TL;DR
This study demonstrates that GPT-4, a large language model, can interpret novel literary metaphors with high accuracy, showing emergent creative reasoning abilities comparable to human experts.
Contribution
It provides evidence that LLMs can interpret complex, novel metaphors, revealing emergent creative and interpretive capabilities not explicitly trained for.
Findings
GPT-4 produced superior metaphor interpretations compared to college students.
GPT-4's interpretations were rated as good or excellent by literary critics.
Both GPT-4 and humans showed sensitivity to the Gricean cooperative principle in metaphor interpretation.
Abstract
Recent advances in the performance of large language models (LLMs) have sparked debate over whether, given sufficient training, high-level human abilities emerge in such generic forms of artificial intelligence (AI). Despite the exceptional performance of LLMs on a wide range of tasks involving natural language processing and reasoning, there has been sharp disagreement as to whether their abilities extend to more creative human abilities. A core example is the ability to interpret novel metaphors. Given the enormous and non curated text corpora used to train LLMs, a serious obstacle to designing tests is the requirement of finding novel yet high quality metaphors that are unlikely to have been included in the training data. Here we assessed the ability of GPT4, a state of the art large language model, to provide natural-language interpretations of novel literary metaphors drawn from…
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Language, Metaphor, and Cognition
MethodsMulti-Head Attention · Attention Is All You Need · Network On Network · Linear Layer · Adam · Dense Connections · Label Smoothing · Residual Connection · Dropout · Absolute Position Encodings
