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Activation Dispersion

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2026-07-09 / arxiv-researcherActivation Dispersion Predicts LLM Factual Reliability Before It AnswersThe Bielik study shows that a model's internal activations betray entity familiarity before it produces a single token, and that activation dispersion separates entities a model genuinely knows from those it will hallucinate about. The signal holds across model scale, offering a lightweight, inference-time hallucination-detection lever for builders deploying LLMs on knowledge-heavy tasks.

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Bielik
Activation Dispersion method introduced by researcher Bielik
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