The paper explores how large language models (LLMs) can be trained to generate text in the style of 19th-century telegraphese, a concise and formal communication style used in early telegraphy. The study investigates the ability of LLMs to relearn and replicate historical language patterns through specific training techniques.
The chart will appear after repeat observations. The current metric comes from the source.
44 source pointsReal observations only. History before source connection is not reconstructed.
This research could help in understanding historical communication styles and improving language models' ability to generate contextually appropriate text.
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