Use the local Jacobian of a looped transformer to estimate its remaining relaxation time and stop the recurrent computation when the predicted residual reduction is sufficient. Near a saddle-node fold, the paper's asymptotic relation converts an estimated dominant eigenvalue into a compute forecast, allowing dynamic iteration budgets instead of a conservative fixed maximum.
Add a local Jacobian spectral regularizer and an initialization sweep to steer a looped transformer away from uncontrolled near-unit dynamics. The goal is to prevent examples from entering a fold-critical regime with very long relaxation times, or alternatively to deliberately target a controlled critical regime when adaptive test-time compute is useful.