mlsanityData to 14 Oct 2026

Large Language Model Displays Emergent Ability to Interpret Novel Literary Metaphors

arXiv 2308.01497 ↗First posted 3 Aug 2023cs.CLcited by 12

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Abstract (arXiv)

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 Serbian poetry and translated into English. Despite exhibiting no signs of having been exposed to these metaphors previously, the AI system consistently produced detailed and incisive interpretations. Human judges, blind to the fact that an AI model was involved, rated metaphor interpretations generated by GPT4 as superior to those provided by a group of college students. In interpreting reversed metaphors, GPT4, as well as humans, exhibited signs of sensitivity to the Gricean cooperative principle. In addition, for several novel English poems GPT4 produced interpretations that were rated as excellent or good by a human literary critic. These results indicate that LLMs such as GPT4 have acquired an emergent ability to interpret complex metaphors, including those embedded in novel poems.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 11 of its 57 references that are in the map. First posted on arXiv 3 Aug 2023.

Builds on

11 of 57 references.

References · 11

  1. 2017Attention Is All You Needcited by 60,361
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  3. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,592
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  11. 2022Psychologically-informed chain-of-thought prompts for metaphor understanding in large language modelscited by 14

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 2; 2025: 4; 2026: 5.

12 papers.