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This arXiv preprint analyzes the historical development of spoken political language in the United States, likely employing computational or linguistic methods.
The article introduces the word 'zuzai' as a term to describe things free from AI, aiming to fill a linguistic gap for indicating the absence of AI in an era of its proliferation.
The authors use an iterated learning model to study how meaning frequency affects the emergence of compositionality, expressivity, and stability in evolved languages. They find that high-frequency whole meanings escape grammatical pressure, but frequency applied to sub-meaning parts leads to transmission failure.
This paper presents multi-agent simulations of the emergence of morphological alternation patterns (like 'go/went') in language, using an AI Historical Linguist (LLM-driven) to evaluate plausibility of evolved morphologies against real languages.