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block

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

block appears in the code Syntology harvested for 17 papers, as 21 distinct code bodies found in 25 places (a place is one code body under one paper). At least one of them ran in 8 of the papers; 4 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 block 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 8 of the 21 distinct code bodies named block; 13 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

1ran · honoured contract
0ran · violated contract
1ran · our draft was wrong
2ran · fixture could not drive it
4ran
13unverified
4fingerprinted

Licence is a property of each copy, so it is counted per place: 7 of the 25 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

17 papers shown of 17, newest first; 25 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. 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
Can We Get Rid of Handcrafted Feature Extractors? SparseViT: Nonsemantics-Centered, Parameter-Efficient Image Manipulation Localization through Spare-Coding Transformer 19 Dec 2024 scu-zjz/sparsevit/SparseViT.py d6288c615374bd37 ran · fixture could not drive it fingerprinted CC-BY-4.0 · pointer only
Window-Based Early-Exit Cascades for Uncertainty Estimation: When Deep Ensembles are More Efficient than Single Models 14 Mar 2023 keras-team/keras/keras/src/applications/efficientnet.py c84bba05a0e9fe98 unverified Apache-2.0 (permissive)
Partial Identification of Treatment Effects with Implicit Generative Models 14 Oct 2022 rgklab/partial_identification/model/common.py 38d07db83707373f unverified MIT (permissive)
Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes 8 Sep 2022 tipt0p/three_regimes_on_the_sphere/nets/convnet.py e9d3b739701f64b2 unverified Apache-2.0 (permissive)
Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes 8 Sep 2022 tipt0p/three_regimes_on_the_sphere/nets/convnet_si.py f9e345905349850a unverified Apache-2.0 (permissive)
Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes 8 Sep 2022 tipt0p/three_regimes_on_the_sphere/nets/convnet_si_af.py bf9fa9508b358457 unverified Apache-2.0 (permissive)
Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes 8 Sep 2022 tipt0p/three_regimes_on_the_sphere/nets/convnet_nobn.py a37fca5fb609181f unverified Apache-2.0 (permissive)
MaxViT: Multi-Axis Vision Transformer 4 Apr 2022 qwopqwop200/MaxVIT-pytorch/MaxVIT.py 5d26f1a66e6a15e4 unverified MIT (permissive)
Multiscale mobility patterns and the restriction of human movement 2022-01 (from id) barahona-research-group/pygenstability/examples/multiscale_example.py e8ad4b6bbe2762e0 ran · honoured contract GPL-3.0 (copyleft) · pointer only
On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay 29 Jun 2021 tipt0p/periodic_behavior_bn_wd/nets/convnet.py e9d3b739701f64b2 unverified Apache-2.0 (permissive)
On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay 29 Jun 2021 tipt0p/periodic_behavior_bn_wd/nets/convnet_si.py f9e345905349850a unverified Apache-2.0 (permissive)
On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay 29 Jun 2021 tipt0p/periodic_behavior_bn_wd/nets/convnet_si_af.py bf9fa9508b358457 unverified Apache-2.0 (permissive)
RepVGG: Making VGG-style ConvNets Great Again 11 Jan 2021 imad08/Repvgg_pytorch/block.py a057a0ac99341954 ran fingerprinted no licence file found · pointer only
Expressive Power of Invariant and Equivariant Graph Neural Networks 28 Jun 2020 mlelarge/graph_neural_net/models/blocks_emb.py d7331e9b86e16f47 ran · our draft was wrong Apache-2.0 (permissive)
Expressive Power of Invariant and Equivariant Graph Neural Networks 28 Jun 2020 mlelarge/graph_neural_net/models/blocks_emb.py f93f27ccbc08cab8 unverified Apache-2.0 (permissive)
Rethinking Parameter Counting in Deep Models: Effective Dimensionality Revisited 4 Mar 2020 g-benton/hessian-eff-dim/hess/nets/convnet.py e9d3b739701f64b2 unverified Apache-2.0 (permissive)
FDFtNet: Facing Off Fake Images using Fake Detection Fine-tuning Network 5 Jan 2020 cutz-j/FDFtNet/fdft/mb_block.py 2ff9af83709add88 unverified MIT (permissive)
Self-Supervised Learning of Pretext-Invariant Representations 4 Dec 2019 kawshik8/DL-project/src/SSLmodels.py 12dbacdbe04e3d37 ran · metamorphic tier: deterministic fingerprinted no licence file found · pointer only
Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression 19 Nov 2019 grifon-239/diploma/common/backbones/efficientnet.py 1f6b117f42a0ded5 unverified MIT (permissive)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 Burf/EfficientNet-Lite-Tensorflow2/effnet/effnet.py c7e2a34a498dc9c6 ran · fixture could not drive it MIT (permissive)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 marcointrovigne/WeatherDetection/net/efficientnet.py 3dd1a3bf20911c40 unverified no licence file found · pointer only
End-to-End Incremental Learning 25 Jul 2018 axelmukwena/biometricECG/cnn.py 2acfc8cd3d4a7a41 unverified MIT (permissive)
Deep Residual Learning for Image Recognition 10 Dec 2015 AyushAniket/ResNET-and-various-normalizations/train_cifar.py bd1ee2bf95c03fa0 ran no licence file found · pointer only
Deep Residual Learning for Image Recognition 10 Dec 2015 ry/tensorflow-resnet/resnet.py a8c9cf7f87940088 unverified MIT (permissive)
U-Net: Convolutional Networks for Biomedical Image Segmentation 18 May 2015 berenslab/retinal-vessel-segmentation-benchmark/networks/fr_unet.py 7ad191ef157bae33 ran fingerprinted no licence file found · pointer only

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