Bibliographic record
Abstract
There has been a lot of interest of late for programming languages that incorporate features from dependent type systems and proof assistants, in order to capture important invariants of the program in the types. This allows type-based program verification and is a promising compromise between plain old types and full blown Hoare logic proofs. The introduction of GADTs in GHC (and more recently type families) made such dependent typing available in an industry-quality implementation, making it possible to consider its use in large scale programs. We have undertaken the construction of a complete compiler for System F , whose main property is that the GHC type checker verifies mechanically that each phase of the compiler properly preserves types. Our particular focus is on "types rather than proofs": reasonably few annotations that do not overwhelm the actual code. We believe it should be possible to write such a type-preserving compiler with an amount of extra code comparable to what is necessary for typical typed intermediate languages, but with the advantage of static checking. We will show in this paper the remaining hurdles to reach this goal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".