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arXiv cs.LG
arXiv cs.LG
6/25/2026
Conformal Orbit-Valid Trust Horizons for Equivariant World Models

Conformal Orbit-Valid Trust Horizons for Equivariant World Models

Short summary

This research paper develops a conformal-prediction method for certifying trust horizons in learned world models—the horizons over which rollouts remain accurate. The key insight is that equivariance properties enable trust certificates to transfer across group symmetries with minimal error (1–4% empirically). Empirical validation across 50+ trials shows non-vacuous certificates with zero anti-conservative violations.

  • •Conformal prediction method certifies when learned world models are trustworthy over specific horizons
  • •Equivariance properties enable trust certificates to transfer across group symmetries with <5% error
  • •Empirical validation shows zero violations across 50 audits—advancing reliable AI system validation

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