ACPC, a rollout-consistency diagnostic for JEPA world models, bounds perturbation-induced prediction-error and planning-cost changes and, together with IR and SR, identifies checkpoints that stay robust under visual perturbations.
Imagined Rollouts are Kinematic, Not Dynamic: A Diagnosis of Long-Horizon World-Model Failure
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Long-horizon failure in world models is conventionally attributed to compounding error, a generic framing that does not distinguish what kind of error compounds. We propose a kinematic-vs-dynamic reframing: world models tend to imagine kinematically rather than dynamically. We operationalize this as the imagined Kinematic-Consistency Error, a per-step diagnostic that measures how far a rollout departs from a closed-form kinematic null, paired with a perturbation protocol that tests whether iKCE responds when physical conditions cross a regime boundary. We instantiate the diagnostic on a released DreamerV3 checkpoint trained on DMC walker-walk, where imagined iKCE runs roughly two orders of magnitude above that of matched real-physics rollouts. Across a friction sweep that crosses the gait-collapse boundary, the model's iKCE stays statistically flat even as the trained policy's reward collapses through the same range, providing the kinematic-not-dynamic signature. The diagnostic distinguishes kinematic from dynamic imagination at horizons longer than the embodiment's gait period.
fields
cs.LG 1years
2026 1verdicts
ACCEPT 1representative citing papers
citing papers explorer
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Diagnosing JEPA World Models with Action-Conditioned Predictive Consistency
ACPC, a rollout-consistency diagnostic for JEPA world models, bounds perturbation-induced prediction-error and planning-cost changes and, together with IR and SR, identifies checkpoints that stay robust under visual perturbations.