Very cool to see @sethkarten's work on continual harnesses
He used ARC-AGI-3 to study two questions:
1. Can Continual Harness discover hidden rules in games designed to be unknown at test time?
2. Which part of Continual Harness contributes most to its long-horizon progress?
They found two things that made CH outperform baselines:
1. Reusable skills turn discovered mechanics into efficient execution routines
2. Reset-free refinements that improve the harness's world model as trajectories grow longer
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