Proceedings of the tenth ACM SIGPLAN international conference on Functional programming
Bibliographic record
Abstract
This volume collects the papers presented at the 10th ACM SIGPLAN International Conference on Functional Programming, ICFP'05, which took place from September 26 to 28 in Tallinn, Estonia.ICFP covers the art and science of functional programming-from principles to practice, from foundations to features, and from abstraction to application. Its scope includes all languages that encourage programming with functions, including both purely applicative and imperative languages, as well as languages with objects and concurrency.There were 87 submissions from Europe, Asia, Canada, and the United States. From these, during a two-day meeting held in Philadelphia, the program committee selected 26 papers for presentation. Each paper was read by at least three program committee members and one external reviewer. Following last year's experiment, the reviews were made available before the program committee meeting, and authors were given the opportunity to add up to 500 words of their own comments and responses to reviewer queries. On the whole, both authors and PC members felt that this round of comments made a useful contribution to the paper selection process.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".