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DreamLedger: Where to Refuse World-Model Imagination Using Execution-Settled Credit

arXiv · AI, language, vision and robotics · article · Aug 24, 2026 · UTC

World-model predictions inform robot actions, yet instantaneous reliability signals do not retain the outcomes of comparable past predictions. DreamLedger registers consumed predictions as claims, settles them against execution outcomes, and uses persistent execution history from comparable operating conditions, regions, and prediction horizons to estimate credit before future reliance. Replayable records connect each decision to its supporting evidence and eventual outcome. In ten-seed navigation comparisons at matched refusal volume, removing history features or resetting history increases b

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