Extracting Operator Trees from Model Embeddings

Abstract

Transformer-based language models are able to capture several linguistic properties such as hierarchical structures like dependency or constituency trees. Whether similar structures for mathematics are extractable from language models has not yet been explored. This work aims to probe current state-of-the-art models for the extractability of Operator Trees from their contextualized embeddings using the structure probe designed by (Hewitt and Manning, 2019). We release the code and our data set for future analyses.