Large Language Model Displays Emergent Ability to Interpret Novel Literary Metaphors
CoRR(2023)
摘要
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.
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关键词
literary,novel
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