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 GPT-4,
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 judge - blind to the fact that an AI model was
involved - rated metaphor interpretations generated by GPT-4 as superior to
those provided by a group of college students. In interpreting reversed
metaphors, GPT-4, as well as humans, exhibited signs of sensitivity to the
Gricean cooperative principle. These results indicate that LLMs such as GPT-4
have acquired an emergent ability to interpret complex novel metaphors.

通过评估 GPT-4，一个尖端的大型语言模型，在解释塞尔维亚诗歌中提取的新颖文学隐喻时所提供的自然语言解释能力，它未展现出之前接触过这些隐喻的迹象，但提供了详细而深刻的解释，被盲审的人员（不知道涉及 AI 模型的事实）将 GPT-4 生成的隐喻解释评为优于来自一组大学生的解释，这些结果表明 GPT-4 等大语言模型已经获得了解释复杂新颖隐喻的新兴能力。