are hallucinations actually “compression tension” in LLMs?

compression-aware intelligence suggests the real problem isn’t just hallucinations, it’s instability under variation.

a model can give a correct answer once but if small changes in phrasing cause it to resolve that underlying tension differently, you get contradictions. that’s the signal that the compression hasn’t actually reconciled the underlying patterns. instead of “is this answer correct?” the new question becomes: “does this answer stay consistent when the same meaning is expressed differently?” using compression tension score (CTS)