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ChronoLens is a framework using multilingual language models and crosscoders to measure historical language change across linguistic levels in 44.98 million documents from five parliamentary traditions (1803–2026), showing that change magnitude and direction vary across languages and time.
This paper investigates how the growing use of LLMs in writing is altering scientific communication, using a corpus of ACL papers and synthetic data to show lexical and stylistic changes, and connects these to subjective reading experience via expert annotations.
The author investigates how LLMs are influencing word usage in coding and everyday language, finding that words favored by LLMs show increased frequency in both coding sessions and Google Trends, raising concerns about humans adopting LLM writing styles.