---
title: "Systematicity between Forms and Meanings across Languages"
description: "The authors keep IB's accuracy term but replace its complexity term with a learnability-based measure. 188 references."
authors: ["Doreen Osmelak", "Yang Xu", "Michael Hahn", "Kate McCurdy"]
year: 2026
venue: "Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)"
source: "https://aclanthology.org/2026.acl-long.1340/"
doi: "10.18653/v1/2026.acl-long.1340"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/osmelak-2026-systematicity-between-forms-meanings-across/"
---
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# Systematicity between Forms and Meanings across Languages Supports Efficient Communication

**Authors:** Doreen Osmelak, [Yang Xu](https://md.research.elamur.ai/free/en/authors/yang-xu/), [Michael Hahn](https://md.research.elamur.ai/free/en/authors/michael-hahn/) and Kate McCurdy · **Year:** 2026 · **Venue:** [Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)](https://md.research.elamur.ai/free/en/venues/acl/) ([ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.acl-long.1340/) · [PDF](https://aclanthology.org/2026.acl-long.1340.pdf) · [DOI 10.18653/v1/2026.acl-long.1340](https://doi.org/10.18653/v1/2026.acl-long.1340) · [OpenAlex](https://openalex.org/W7166848910)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
Research on efficient communication shows that lexicons balance simplicity against accuracy. Its standard formalization, the Information Bottleneck (IB) model, treats word forms as unanalysable symbols. As a result, IB can only detect syncretism (one form shared by several meanings), not partial, systematic overlap such as a prefix that consistently marks person.

The authors keep IB's accuracy term but replace its complexity term with a learnability-based measure. A character-level sequence-to-sequence network learns to map morphosyntactic feature bundles (person, number, gender) to surface forms. Complexity is the cross-entropy training loss averaged over epochs and weighted by corpus-derived need frequencies (CETL).

They apply this to verb paradigms (Semitic/Afro-Asiatic, Romance, Germanic) and to pronoun systems across hundreds of languages, comparing attested paradigms against structural and form-only permutations. Attested systems prove more efficient than these counterfactuals, and paradigms with more natural syncretism are easier to learn. CETL also separates real from artificial paradigms much better than IB. The work bridges efficiency theory and language-evolution findings on systematicity.

## Key points
- **Form-only permutations:** CETL rated 65.81%, 89.21% and 78.23% of permutations as less efficient than the original in the three domains (PPD, PRON, VERB). IB cannot separate these permutations by design, so its performance score (correct minus incorrect) is −100 in every domain.
- **Structural permutations:** CETL beat IB consistently in identifying attested paradigms as more efficient.
- **Naturalness:** averaged per-language correlations between CETL and unnaturalness were 0.36 (PPD), 0.82 (PRON) and 0.88 (VERB). For Afro-Asiatic verbs, ρ = 0.5745. IB showed no correlation for PRON or VERB.
- **Evaluation domains:** inflectional verb morphology (both concatenative and templatic Semitic) and pronouns. The pronoun analysis allows direct comparison with Zaslavsky et al. (2021b).
- **Limitations:** the method covers only discrete paradigmatic domains, not continuous ones like color. It builds no Pareto frontier and does not replicate IB's feature-weight optimization.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

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## Cite

Cite as: Doreen Osmelak, Yang Xu, Michael Hahn and Kate McCurdy. 2026. Systematicity between Forms and Meanings across Languages Supports Efficient Communication. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{osmelak2026systematicity,
  title = {{Systematicity between Forms and Meanings across Languages Supports Efficient Communication}},
  author = {Doreen Osmelak, Yang Xu, Michael Hahn and Kate McCurdy},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.acl-long.1340},
  url = {https://doi.org/10.18653/v1/2026.acl-long.1340}
}
```

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- [↑ back to papers of 2026](https://md.research.elamur.ai/free/en/papers/2026/page/44/)

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*Updated 1 November 2026*