用大模型将词典嵌入语义图，研究符号接地问题
Approaching the Source of Symbol Grounding with Confluent Reductions of Abstract Meaning Representation Directed Graphs
- 用大模型将数字词典映射到语义图中
- 通过保环变换压缩语义图结构
- 揭示语义图性质与符号接地的关系
语义抽象表示（AMR）是一种将句子意义表示为有向无环图的语义形式。本文描述如何利用先进的预训练大语言模型，将真实数字词典嵌入到AMR有向图中。随后，以保环方式对这些图进行约简，即保持其电路空间不变的变换。最后，分析并讨论约简后图的性质，探讨其与符号接地问题的关系。
原文摘要 · Abstract (English)
Abstract meaning representation (AMR) is a semantic formalism used to represent the meaning of sentences as directed acyclic graphs. In this paper, we describe how real digital dictionaries can be embedded into AMR directed graphs (digraphs), using state-of-the-art pre-trained large language models. Then, we reduce those graphs in a confluent manner, i.e. with transformations that preserve their circuit space. Finally, the properties of these reduces digraphs are analyzed and discussed in relation to the symbol grounding problem.
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