LLM在缺乏接地情况下的感知结构：颜色语言中抽象性与主观性的影响
Perceptual Structure in the Absence of Grounding for LLMs: The Impact of Abstractedness and Subjectivity in Color Language
AI总结：
本文通过近100万颜色描述样本，实证比较了跨空间和内部空间两种对齐方式，发现颜色空间对齐在主观性和抽象性强的真实语言使用中显著下降，表明此类情况需要接地。
摘要：
语言理解中的接地需求是一个活跃的研究课题。先前的研究表明，鉴于颜色感知的认知重要性，颜色感知和颜色语言似乎是实证研究该问题的合适测试床，并表明在定义的颜色空间与语言模型定义的特征空间之间存在相当大的对齐。为了进一步研究这个问题，我们收集了一个大规模的颜色及其描述数据源，包含近100万个样本，并进行实证分析以比较两种对齐方式：通过学习嵌入空间与颜色空间之间的映射来实现的跨空间对齐；以及通过在颜色描述之间提示比较来实现的内部空间对齐。我们的结果表明，虽然颜色空间对齐对于单词汇、高度实用的颜色描述成立，但在存在表现出真实语言使用元素（如主观性和抽象性）的样本时，这种对齐会显著下降，这表明在这种情况下可能需要接地。
英文摘要：
The need for grounding in language understanding is an active research topic. Previous work has suggested that color perception and color language appear as a suitable test bed to empirically study the problem, given its cognitive significance and showing that there is considerable alignment between a defined color space and the feature space defined by a language model. To further study this issue, we collect a large scale source of colors and their descriptions, containing almost a 1 million examples , and perform an empirical analysis to compare two kinds of alignments: (i) inter-space, by learning a mapping between embedding space and color space, and (ii) intra-space, by means of prompting comparatives between color descriptions. Our results show that while color space alignment holds for monolexemic, highly pragmatic color descriptions, this alignment drops considerably in the presence of examples that exhibit elements of real linguistic usage such as subjectivity and abstractedness, suggesting that grounding may be required in such cases.
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。
