# The risks of mixing dependency lengths from sequences of different length

arXiv: https://arxiv.org/abs/1304.3841 · HTML: https://mlsanity.com/paper/1304.3841/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Apr 2013.

## Built on by (most cited first, 7 of 7)

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- [Phylogenetic typology](https://mlsanity.com/paper/2103.10198/) (2021)
- [The distribution of syntactic dependency distances](https://mlsanity.com/paper/2211.14620/) (2022)
- [The expected sum of edge lengths in planar linearizations of trees. Theory and applications](https://mlsanity.com/paper/2207.05564/) (2022)
- [Work Smarter...Not Harder: Efficient Minimization of Dependency Length in SOV Languages](https://mlsanity.com/paper/2404.18684/) (2024)
- [The Impact of Edge Displacement Vaserstein Distance on UD Parsing Performance](https://mlsanity.com/paper/2209.07139/) (2022)

## Abstract (arXiv)

Mixing dependency lengths from sequences of different length is a common practice in language research. However, the empirical distribution of dependency lengths of sentences of the same length differs from that of sentences of varying length and the distribution of dependency lengths depends on sentence length for real sentences and also under the null hypothesis that dependencies connect vertices located in random positions of the sequence. This suggests that certain results, such as the distribution of syntactic dependency lengths mixing dependencies from sentences of varying length, could be a mere consequence of that mixing. Furthermore, differences in the global averages of dependency length (mixing lengths from sentences of varying length) for two different languages do not simply imply a priori that one language optimizes dependency lengths better than the other because those differences could be due to differences in the distribution of sentence lengths and other factors.