Counterexample-Guided Partial Bounding for Recursive Function Synthesis
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Quantifier bounding is a standard approach in inductive program synthesis in dealing with unbounded domains. In this paper, we propose one such bounding method for the synthesis of recursive functions over recursive input data types. The synthesis problem is specified by an input reference (recursive) function and a recursion skeleton . The goal is to synthesize a recursive function equivalent to the input function whose recursion strategy is specified by the recursion skeleton. In this context, we illustrate that it is possible to selectively bound a subset of the (recursively typed) parameters, each by a suitable bound. The choices are guided by counterexamples. The evaluation of our strategy on a broad set of benchmarks shows that it succeeds in efficiently synthesizing non-trivial recursive functions where standard across-the-board bounding would fail.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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