Linguistic Illegibility in Large Language Models: Implications for Security

The paper explores how large language models (LLMs) may exhibit linguistic illegibility, where their outputs and extracted features fail to accurately reflect internal computations. It argues that this necessitates alternative security approaches like taint tracking and sandboxing, as traditional linguistic monitoring mechanisms are inherently unreliable.

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