Bibliographic record
Abstract
It is our great pleasure to welcome you to the 32nd International Conference on Parallel Architectures and Compilation Techniques -PACT 2023.PACT is a unique technical conference sitting at the intersection of hardware and software, with a special emphasis on parallelism.Topics on computer architecture, memory systems, and compilers continue to be of much interest to researchers from academia and industry.This year we received 66 completed submissions (out of 124 abstract submissions), a low number relative to historical data.The Steering Committee is looking to the causes for such a low submission rate and will provide suggestions to future chairs.The program committee consisted of 40 experts from across academia, industry, and government research laboratories.We used a paper bidding process backed up by the Toronto Paper Matching System (http://torontopapermatching.org).We had two rounds of reviews, with author notifications for rejected papers after the first round.The program committee held online discussions and a 2-session virtual PC meeting to accommodate time zones across the globe.For the final program, the program committee invited 25 full papers and 15 posters.Seven of the poster authors chose to withdraw their work.The work that is presented in the conference spans all the topics of interests for PACT.
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.
How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.001 |
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 teacher head, 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".