Separating controlled divergence from evidence-governed absorption reduces persona-environment self-locking, cutting macro-theme repetition from 61.8% to 36.3% in a same-runtime 40-day A/B.
One fish, two fish, but not the whole sea: Alignment reduces language models’ conceptual diversity
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AutoPersonas: A Multi-Timescale Loop Engine for Open-Ended Persona Evolution
Separating controlled divergence from evidence-governed absorption reduces persona-environment self-locking, cutting macro-theme repetition from 61.8% to 36.3% in a same-runtime 40-day A/B.