The Implications of Linguistic Illegibility for LLM Security
LLMs are trained to generate natural language. However, various strands of evidence indicate that an LLM's externalized linguistic outputs and mechanistically-extracted linguistic features can be an unreliable lens for understanding internal model computation. We introduce the term ``linguistic illegibility'' to broadly refer to scenarios in which an LLM's externalized or mechanistically-probed language artifacts fail to represent how the model actually thinks. We argue that the specter of linguistic illegibility is unavoidable for LLMs whose internal computations are not directly expressed via language, but rather math over activation spaces (with lossy translations between activation sp...
| Authors | James Mickens |
|---|---|
| Primary category | cs.LG |
| Published | 2 September 2026 |
| Last updated at source | 6 October 2026 |
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