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This research proposes a framework where lexical meanings and composition functions co-evolve under pressures for simplicity and accuracy, specifically within the context of evolutionary semantics. By applying this model to quantificational meaning, the study demonstrates how fundamental semantic universals like conservativity emerge as efficient system-wide abstractions rather than fixed constraints. The work bridges formal semantics with evolutionary modeling, offering a template for analyzing how grammatical categories develop global compression and semantic specialization through co-evolutionary processes.
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Compositionality and the lexicon in evolutionary semantics

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arXiv:2606.27228v2 Announce Type: replace Abstract: Formal semantics has shown that sentence meanings arise by recursively composing lexical meanings, yet much of the literature on semantic universals models either lexicons with fixed signal structures or holistic composition without interpretable lexical parts. We introduce a framework that integrates this fundamental insight of formal semantics in evolutionary modeling, by allowing lexical meanings and a composition function to co-evolve under pressures for conceptual simplicity and communicative accuracy. We apply this framework to the evolution of quantificational meaning. Analyzing the Pareto frontier, we find that the most well-known semantic universal, conservativity, emerges as an efficient system-wide abstraction. The account is sensitive to syntactic structure and helps reconcile tensions between empirical evidence on quantifier learnability and prior evolutionary models. More broadly, the results demonstrate that the picture of sentential meaning developed in formal semantics can be productively combined with evolutionary modeling. The framework offers a template for studying universals that involve global compression within a grammatical category, semantic specialization of syntactic arguments, and the co-evolution of lexical and compositional meaning.

Abstract:Formal semantics has shown that sentence meanings arise by recursively composing lexical meanings, yet much of the literature on semantic universals models either lexicons with fixed signal structures or holistic composition without interpretable lexical parts. We introduce a framework that integrates this fundamental insight of formal semantics in evolutionary modeling, by allowing lexical meanings and a composition function to co-evolve under pressures for conceptual simplicity and communicative accuracy. We apply this framework to the evolution of quantificational meaning. Analyzing the Pareto frontier, we find that the most well-known semantic universal, conservativity, emerges as an efficient system-wide abstraction. The account is sensitive to syntactic structure and helps reconcile tensions between empirical evidence on quantifier learnability and prior evolutionary models. More broadly, the results demonstrate that the picture of sentential meaning developed in formal semantics can be productively combined with evolutionary modeling. The framework offers a template for studying universals that involve global compression within a grammatical category, semantic specialization of syntactic arguments, and the co-evolution of lexical and compositional meaning.

Computation and Language (cs.CL)

arXiv:2606.27228 [cs.CL]

(or arXiv:2606.27228v2 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2606.27228 Focus to learn more arXiv-issued DOI via DataCite

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