SciCode/CritPt-style tasks proposed as training targets for verifiable scientific reasoning
geoffwolfe · x · 2026-10-02
ReasonCoreAI argues the impedance mismatch between models and science is itself a training target: use SciCode- and CritPt-style tasks to turn scientific reasoning into executable calculations, respect physical constraints, and check results rather than merely produce plausible explanations.
Suggested approach:
- Train on fresh, expert-validated problems and test on held-out ones to avoid contamination
- BootLoops shows why the eval harness matters
- Domain experts still decide whether a correct calculation answers a worthwhile question
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