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AI research agents are increasingly used to search over programs, mathematical constructions, and proofs. However, existing systems typically optimize evaluator feedback without adequately governing how that feedback is interpreted, challenged, and reused. As a result, promising but fragile candidates can be promoted a...
This work preserves four frozen LoRA branches, each derived from a different post-training trajectory, to provide evidence that post-training branches, even without co-training, can be collectively beneficial for deployment.
Prefix recovery provides a practical diagnostic for selecting costly distribution-level distillation and has the greatest headroom when correct traces remain unevenly recoverable when distribution matching has the greatest headroom.
The result is an auditable division of labor: models widen the search for removable code, order bounds the damage a mis-ranked proposal can do, and execution retains authority over every committed deletion.
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