Selective Execution with Answer-Determined Termination for Structured Reasoning

Reasoning systems spend more computation on problems that look harder, yet how much a problem needs is fixed by the answer it asks for. Once every explanation compatible with the observations implies the same answer, further reasoning cannot change it. Solvers routinely continue past this point, recovering causal structure, proofs, or complete candidate scores that the question never required; we call this over-solving. Here we formalize answer determination under incomplete information, in the sense of certain answers and partial identification, and show that an answer can be unique while arbitrarily many richer explanations remain open, so a solver can stop earlier and can answer instances whose explanation is unrecoverable. Because possible answers can contract in any monotone pattern, no task-independent rule says which computation to skip; we therefore terminate execution with a task-specific completion rule that fires once the answer is determined, and order the computations before that point with a learned answer-relevance energy. On ACRE, CLUTRR, AlphaGeometry, RAVEN-FAIR, and MNS, this selective execution omits 33.95% to 99.98% of task-specific computation while matching or improving baseline accuracy, with gains of up to 30.99 percentage points. Efficient reasoning depends not only on how fast computations run but on which computations the answer requires.