# Quantifying syntax similarity with a polynomial representation of dependency trees

arXiv: https://arxiv.org/abs/2211.07005 · HTML: https://mlsanity.com/paper/2211.07005/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 36 references that are in the map.
- First posted on arXiv 13 Nov 2022.

## Builds on (most cited first, 1 of 1)

- [Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity](https://mlsanity.com/paper/2003.04866/) (2020)

## Built on by (most cited first, 6 of 6)

- [SCOI: Syntax-augmented Coverage-based In-context Example Selection for Machine Translation](https://mlsanity.com/paper/2408.04872/) (2024)
- [Iconicity in Large Language Models](https://mlsanity.com/paper/2501.05643/) (2025)
- [Ungrammatical-syntax-based In-context Example Selection for Grammatical Error Correction](https://mlsanity.com/paper/2403.19283/) (2024)
- [Going Beyond Word Matching: Syntax Improves In-context Example Selection for Machine Translation](https://mlsanity.com/paper/2403.19285/) (2024)
- [Counting trees: A treebank-driven exploration of syntactic variation in speech and writing across languages](https://mlsanity.com/paper/2505.22774/) (2025)
- [Measuring language complexity from hierarchical reuse of recurring patterns](https://mlsanity.com/paper/2606.11531/) (2026)

## Abstract (arXiv)

We introduce a graph polynomial that distinguishes tree structures to represent dependency grammar and a measure based on the polynomial representation to quantify syntax similarity. The polynomial encodes accurate and comprehensive information about the dependency structure and dependency relations of words in a sentence. We apply the polynomial-based methods to analyze sentences in the Parallel Universal Dependencies treebanks. Specifically, we compare the syntax of sentences and their translations in different languages, and we perform a syntactic typology study of available languages in the Parallel Universal Dependencies treebanks. We also demonstrate and discuss the potential of the methods in measuring syntax diversity of corpora.