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clipped_zoom

Syntologyentry name in harvested coderead from the graph 2026-09-24

clipped_zoom appears in the code Syntology harvested for 13 papers, as 6 distinct code bodies found in 15 places (a place is one code body under one paper). At least one of them ran in 12 of the papers; 5 of the code bodies carry a behaviour fingerprint.

What this page is not. Routines are grouped here by the exact string of their function or class name. Nothing asserts that two samples named clipped_zoom do the same thing, share code, or are comparable; the name is a string, not an identity. Behaviour outputs (what a fingerprinted sample returned on the shared battery) are not in this export and are not shown here; the graph at syntology.ai holds them. "Ran" means executed on a synthesized fixture, not that the code is correct or reproduces a paper.

Samples Syntology

Syntology ran 5 of the 6 distinct code bodies named clipped_zoom; 1 is unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
4ran · our draft was wrong
0ran · fixture could not drive it
1ran
1unverified
5fingerprinted

Licence is a property of each copy, so it is counted per place: 6 of the 15 places are pointer only (Syntology does not serve that copy's text). This site shows no code text for any sample; every row below links to the file in its repository where the record names one.

“Ran” means the sample executed on a synthesized input; it does not mean the output is correct. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code, and those samples did run. The ran count above is every status except unverified, the same rule as each paper page.

Papers

13 papers shown of 13, newest first; 15 places in the table. A paper with no recorded date is placed by the month its arXiv id encodes, shown in the Date column as YYYY-MM (from id). One row per place: a paper whose repository defines the name more than once appears more than once, and the same code body held for several papers appears once under each, with the same status. Titles and dates are the archive's archive 2025-07-28 for papers in the archive, and the graph's for 2 papers added by Syntology; 1 papers have no page here and are shown by arXiv id only. Status and fingerprint are Syntology's record of each code body; licence is recorded for each place. The File cell ends with the code body's code_sha256, Syntology's identity for that exact code: an agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

PaperDateFileStatus SyntologyLicence
ActiveSAM: Image-Conditional Class Pruning for Fast and Accurate Open-Vocabulary Segmentation added by Syntology 2026-06 (from id) VILA-Lab/ActiveSAM/activesam/imagecorruptions/corruptions.py 9f1bb16740f8d1ed ran · our draft was wrong fingerprinted MIT (permissive)
Automated Model Evaluation for Object Detection via Prediction Consistency and Reliability added by Syntology 2025-08 (from id) YonseiML/autoeval-det/imagenet_c/corruptions.py 5f0ee8450d2eac09 ran · our draft was wrong fingerprinted no licence file found · pointer only
arXiv:2507.20453 2025-07 (from id) identical code first harvested elsewhere 466ca3cdf4524d82 ran · our draft was wrong fingerprinted licence of this copy not recorded
$\texttt{AVROBUSTBENCH}$: Benchmarking the Robustness of Audio-Visual Recognition Models at Test-Time 31 May 2025 sarthaxxxxx/AV-C-Robustness-Benchmark/corruptions/corruptions.py a146d4bd6b14b2c5 unverified MIT (permissive)
Benchmarking Robustness of Text-Image Composed Retrieval 24 Nov 2023 suntongtongtong/benchmark-robustness-text-image-compose-retrieval/corrupt/utils.py cd9617f1ecbb4b0c ran fingerprinted no licence file found · pointer only
Data Models for Dataset Drift Controls in Machine Learning With Optical Images 4 Nov 2022 aiaudit-org/raw2logit/utils/hendrycks_robustness.py 466ca3cdf4524d82 ran · our draft was wrong fingerprinted MIT (permissive)
A Novel Data Augmentation Technique for Out-of-Distribution Sample Detection using Compounded Corruptions 28 Jul 2022 cnc-ood/cnc_ood/augmentations/corruptions.py 466ca3cdf4524d82 ran · our draft was wrong fingerprinted MIT (permissive)
AugMax: Adversarial Composition of Random Augmentations for Robust Training 26 Oct 2021 VITA-Group/AugMax/augmax_modules/corruptions_cifar.py 466ca3cdf4524d82 ran · our draft was wrong fingerprinted MIT (permissive)
A simple way to make neural networks robust against diverse image corruptions 16 Jan 2020 identical code first harvested elsewhere 5f0ee8450d2eac09 ran · our draft was wrong fingerprinted licence of this copy not recorded
A simple way to make neural networks robust against diverse image corruptions 16 Jan 2020 identical code first harvested elsewhere 466ca3cdf4524d82 ran · our draft was wrong fingerprinted licence of this copy not recorded
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming 17 Jul 2019 bethgelab/imagecorruptions/imagecorruptions/corruptions.py 9f1bb16740f8d1ed ran · our draft was wrong fingerprinted Apache-2.0 (permissive)
MNIST-C: A Robustness Benchmark for Computer Vision 5 Jun 2019 google-research/mnist-c/corruptions.py f210d4ac7d4969d7 ran · our draft was wrong fingerprinted Apache-2.0 (permissive)
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations 28 Mar 2019 hendrycks/robustness/ImageNet-C/imagenet_c/imagenet_c/corruptions.py 5f0ee8450d2eac09 ran · our draft was wrong fingerprinted Apache-2.0 (permissive)
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations 28 Mar 2019 hendrycks/robustness/ImageNet-P/create_p/make_imagenet_p.py 466ca3cdf4524d82 ran · our draft was wrong fingerprinted Apache-2.0 (permissive)
Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations 4 Jul 2018 identical code first harvested elsewhere 9f1bb16740f8d1ed ran · our draft was wrong fingerprinted licence of this copy not recorded

This site shows no code text; each File cell links to the file on GitHub at the repository's current default branch, which may have changed since the harvest. "Pointer only" means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence cell for the reason. Per-sample records for a paper are on its paper page under "Code Syntology ran".

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections