mlsanityData to 14 Oct 2026

Word reuse and combination support efficient communication of emerging concepts

arXiv 2411.05379 ↗First posted 8 Nov 2024cs.CLcited by 2

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Abstract (arXiv)

A key function of the lexicon is to express novel concepts as they emerge over time through a process known as lexicalization. The most common lexicalization strategies are the reuse and combination of existing words, but they have typically been studied separately in the areas of word meaning extension and word formation. Here we offer an information-theoretic account of how both strategies are constrained by a fundamental tradeoff between competing communicative pressures: word reuse tends to preserve the average length of word forms at the cost of less precision, while word combination tends to produce more informative words at the expense of greater word length. We test our proposal against a large dataset of reuse items and compounds that appeared in English, French and Finnish over the past century. We find that these historically emerging items achieve higher levels of communicative efficiency than hypothetical ways of constructing the lexicon, and both literal reuse items and compounds tend to be more efficient than their non-literal counterparts. These results suggest that reuse and combination are both consistent with a unified account of lexicalization grounded in the theory of efficient communication.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 5 of its 99 references that are in the map. First posted on arXiv 8 Nov 2024.

Builds on

5 of 99 references.

References · 5

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  2. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  3. 2016Diachronic Word Embeddings Reveal Statistical Laws of Semantic Changecited by 221
  4. 2021How (Non-)Optimal is the Lexicon?cited by 11
  5. 2018The Road to Success: Assessing the Fate of Linguistic Innovations in Online Communitiescited by 9

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Citing papers per year: 2025: 1; 2026: 1.

2 papers.