A uniform approach for generating proofs and strategies for both true and false QBF formulas
Why this work is in the frame
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Bibliographic record
Abstract
Many important problems can be compactly represented as quantified boolean formulas (QBF) and solved by general QBF solvers. To date QBF solvers have mainly focused on determining whether or not the input QBF is true or false. However, additional important information about an application can be gathered from its QBF formulation. In this paper we demonstrate that a circuitbased QBF solver can be exploited to obtain a QResolution proof of the truth or the falsity of a QBF. QBFs have a natural interpretation as a two person game and our main result is to show how, via a simple computation, the moves for the winning player can be computed directly from these proofs. This result shows that the proof is a representation of the winning strategy. In previous approaches the winning strategy has often been represented in a way that makes it hard to verify. In our approach the correctness of the strategy follows directly from the correctness of the proof, which is relatively easy to verify.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it