语言模型坚守立场：探究具身性对语言模型比喻语言理解的影响
LMs stand their Ground: Investigating the Effect of Embodiment in Figurative Language Interpretation by Language Models
AI总结：
本研究探究具身性对语言模型比喻语言理解的影响，发现隐喻动作具身性越强，大语言模型解读表现越好，排除其他特征共线性干扰，为大模型具备促进比喻理解的具身概念化能力提供了初步证据。
摘要：
比喻语言对语言模型而言是一项挑战，因为其解读依赖于以偏离常规语序和含义的方式使用词汇。然而人类能够轻松理解并阐释隐喻、明喻或习语，因为这些表达可源自具身隐喻。语言是具身性的代理载体，若某一隐喻属于常规化且已词汇化的表达，没有实体的系统也更容易理解具身概念。但在语言模型的比喻语言解读研究语境下，具身性与具体性、习得年龄等特征之间的复杂关联尚未得到探究。因此，本研究表明，当隐喻句子中的动作更具具身性时，更大规模的语言模型在解读隐喻句子方面表现更优。该分析排除了与词长、具体性等其他特征的多重共线性，并提供了初步证据，证明更大规模的语言模型对具身概念的概念化程度足以促进比喻语言理解。
英文摘要：
Figurative language is a challenge for language models since its interpretation is based on the use of words in a way that deviates from their conventional order and meaning. Yet, humans can easily understand and interpret metaphors, similes or idioms as they can be derived from embodied metaphors. Language is a proxy for embodiment and if a metaphor is conventional and lexicalised, it becomes easier for a system without a body to make sense of embodied concepts. Yet, the intricate relation between embodiment and features such as concreteness or age of acquisition has not been studied in the context of figurative language interpretation concerning language models. Hence, the presented study shows how larger language models perform better at interpreting metaphoric sentences when the action of the metaphorical sentence is more embodied. The analysis rules out multicollinearity with other features (e.g. word length or concreteness) and provides initial evidence that larger language models conceptualise embodied concepts to a degree that facilitates figurative language understanding.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
