Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite decades of efforts and successes in logic synthesis, algorithm runtime has rarely been taken as a first class objective in research. As design complexity soars and million gate designs become common, as deep submicron effects dominate and frequently invoking logic synthesis within a low-level physical design environment, or a high-level architectural exploration environment become mandatory, it becomes necessary to revisit the fundamental logic synthesis infrastructure and algorithms. In this paper, we demonstrate FBDD, an open sourced, binary decision diagram (BDD) based logic synthesis package, which employs several new techniques, including folded logic transformations and two-variable sharing extraction. Towards the goal of scaling logic synthesis algorithms, we show that for standard benchmarks, and for field programmable gate array (FPGA) technology, FBDD can produce circuits with comparable area with commercial tools, while running one order of magnitude faster.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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