Large Language Models

Write Like It's 1866: LLMs Relearn Telegraphese

Travis Smith tests whether a one-sentence instruction to answer in cablese, the compressed dialect of telegraph operators, can cut LLM output costs. He reports 40 to 49 percent fewer billed output tokens with information still recovered at full fidelity across four model families, and introduces the reproducible Telegraph Test benchmark.

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