# Memory limitations are hidden in grammar

arXiv: https://arxiv.org/abs/1908.06629 · HTML: https://mlsanity.com/paper/1908.06629/

## Key facts

- Cited by 6 papers in the map (data through 7 Oct 2026).
- First posted on arXiv 19 Aug 2019.

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

- [The Linear Arrangement Library. A new tool for research on syntactic dependency structures](https://mlsanity.com/paper/2112.02512/) (2021)
- [The optimal placement of the head in the noun phrase. The case of demonstrative, numeral, adjective and noun](https://mlsanity.com/paper/2402.10311/) (2024)
- [Linguistic Structure from a Bottleneck on Sequential Information Processing](https://mlsanity.com/paper/2405.12109/) (2024)
- [The expected sum of edge lengths in planar linearizations of trees. Theory and applications](https://mlsanity.com/paper/2207.05564/) (2022)
- [How to measure the optimality of word or gesture order with respect to the principle of swap distance minimization](https://mlsanity.com/paper/2604.01938/) (2026)
- [Formal Constraints on Dependency Syntax](https://mlsanity.com/paper/2604.04542/) (2026)

## Abstract (arXiv)

The ability to produce and understand an unlimited number of different sentences is a hallmark of human language. Linguists have sought to define the essence of this generative capacity using formal grammars that describe the syntactic dependencies between constituents, independent of the computational limitations of the human brain. Here, we evaluate this independence assumption by sampling sentences uniformly from the space of possible syntactic structures. We find that the average dependency distance between syntactically related words, a proxy for memory limitations, is less than expected by chance in a collection of state-of-the-art classes of dependency grammars. Our findings indicate that memory limitations have permeated grammatical descriptions, suggesting that it may be impossible to build a parsimonious theory of human linguistic productivity independent of non-linguistic cognitive constraints.