Quantifying syntax similarity with a polynomial representation of dependency trees
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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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 1 of its 36 references that are in the map. First posted on arXiv 13 Nov 2022.
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Citing papers per year: 2024: 3; 2025: 2; 2026: 1.
6 papers.
- 2024SCOI: Syntax-augmented Coverage-based In-context Example Selection for Machine Translationcited by 1
- 2025Iconicity in Large Language Modelscited by 1
- 2024Ungrammatical-syntax-based In-context Example Selection for Grammatical Error Correctioncited by 0
- 2024Going Beyond Word Matching: Syntax Improves In-context Example Selection for Machine Translationcited by 0
- 2025Counting trees: A treebank-driven exploration of syntactic variation in speech and writing across languagescited by 0
- 2026Measuring language complexity from hierarchical reuse of recurring patternscited by 0
- 2026Measuring language complexity from hierarchical reuse of recurring patterns10 Jun 2026
- 2025Counting trees: A treebank-driven exploration of syntactic variation in speech and writing across languages28 May 2025
- 2025Iconicity in Large Language Models10 Jan 2025
- 2024SCOI: Syntax-augmented Coverage-based In-context Example Selection for Machine Translation9 Aug 2024
- 2024Going Beyond Word Matching: Syntax Improves In-context Example Selection for Machine Translation28 Mar 2024
- 2024Ungrammatical-syntax-based In-context Example Selection for Grammatical Error Correction28 Mar 2024