Position: Natural Language Should Not Fully Replace Formal Languages
A position paper argues that despite advances in LLMs prompting claims that natural language could replace formal languages like programming languages, natural language is optimized for underspecification in open-ended contexts. The authors introduce a framework of 'task specificity', prove a 'specificity crossover theorem', and demonstrate through case studies that natural language excels at low-specificity tasks while formal languages are advantageous for stricter requirements. They conclude that the two are complementary and advocate hybrid systems.
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[Submitted on 10 May 2026]
Title:Position: Natural Language Should Not Fully Replace Formal Languages
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Abstract:Recent advances in large language models and their widespread adoption have prompted claims that natural language could entirely replace formal languages, such as programming languages for software design. In this position paper, we argue that this perspective overlooks fundamental linguistic properties of natural language, specifically that it is optimized for underspecification in open-ended contexts. We introduce a formal framework centered on *task specificity*, defining it as the information-theoretic reduction of uncertainty in an output space -- such as all possible images -- given a user's specific requirements. We prove a *specificity crossover theorem*, showing the existence of a threshold beyond which the cost to express formal requirements into natural language exceeds the cost of direct formal specification. By analyzing case studies across modalities, such as image generation, code synthesis, and audio production, we demonstrate that natural language excels at low specificity tasks, while formal languages are advantageous on tasks with stricter requirements. We conclude that natural and formal languages are complementary tools and advocate the development of hybrid systems that allow users to move across the specificity spectrum.
Comments: To be published in ICML 2026 (position track)
Subjects:
Computation and Language (cs.CL); Programming Languages (cs.PL)
Cite as: arXiv:2607.20432 [cs.CL]
(or arXiv:2607.20432v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2607.20432
arXiv-issued DOI via DataCite
Submission history
From: Eitan Wagner [view email] [v1] Sun, 10 May 2026 15:01:16 UTC (3,332 KB)
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