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Measuring the Value of World-Model Updates: A Counterfactual Utility Protocol for Continual Adaptation

arxiv.org/abs/2609.10954

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Updated 1 h ago · first seen 11 Sept 2026

paper_01M294FNWP8XJS0CH00ZRVBXJN

Published
11 Sept 2026
T1 · 1 h ago
arXiv
2609.10954
T1 · 1 h ago
Category
cs.LG
T1 · 1 h ago

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9 claims · 9 properties

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https://arxiv.org/abs/2609.10954currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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Continual world models must decide whether new data justify changing the model. Fixed replay schedules and prediction-error triggers specify when to update, but neither reveals the value of an individual update: one deployment run cannot show how the same model would have performed at that moment had it held its parameters. We introduce the fork ledger, which branches a deployment stream at pre-registered decision points into matched update and hold continuations under common random numbers. It evaluates both continuations on the same episodes and records $\Delta R = R_{\mathrm{update}} - R_{\mathrm{hold}}$. Always applying one fixed update mechanism lowers return on all three simulated control tasks: CartPole ($-144.0$; checkpoint-bootstrap $95\%$ CI $[-185.4,-116.1]$, against a converged return near $650$), Walker ($-82.8$; $[-101.1,-61.7]$) and Cheetah ($-18.6$; $[-29.0,-6.6]$). Divergence is an outcome of applying the update, so the estimand counts every attempted fork; restricted to the $693$ of $720$ that did not collapse, CartPole and Walker are unchanged in sign ($-113.4$ and $-82.1$) and Cheetah becomes unresolved ($-3.9$; $[-17.5,+13.0]$). The task is the unit of inference: each contributes $240$ attempted forks over five pretrained checkpoints crossed with two drift directions. The ledger makes counterfactual utility observable for a fixed mechanism, allowing triggers to be judged by the updates they select rather than by surprise detection alone.currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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newcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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2609.10954currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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Anqi Peter Li, Kaden KimcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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cs.LGcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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https://arxiv.org/pdf/2609.10954currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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cs.LGcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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11 Sept 2026currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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