Large Language Models Do Not Always Need Readable Language

arXiv:2606.19857v1 Announce Type: new Abstract: Large language models (LLMs) are commonly prompted and interfaced with human-readable natural language, even when the intended reader is another model. This paper investigates whether semantic information can be encoded in compact, non-standard textual forms that sacrifice human readability while remaining recoverable by LLMs. We refer to this class of model-centric textual representations as BabelTele, approached here not as a fixed protocol but as an empirical probe into LLMs' capacity to generate and interpret such representations. Through rea

Source: arXiv cs.CL — read the full report at the original publisher.

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