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shear_y

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

shear_y appears in the code Syntology harvested for 37 papers, as 18 distinct code bodies found in 40 places (a place is one code body under one paper). At least one of them ran in 24 of the papers; 1 of the code bodies carries 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 shear_y 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 12 of the 18 distinct code bodies named shear_y; 6 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
8ran · our draft was wrong
0ran · fixture could not drive it
4ran
6unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 12 of the 40 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

37 papers shown of 37, newest first; 40 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 1 papers added by Syntology; 3 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
Rethinking Loss Reweighting for Imbalance Learning as an Inverse Problem: A Neural Collapse Point of View added by Syntology 2026-05 (from id) tongzixin716716/Inverse-Loss-Reweighting/randaugment.py e31c4b500a240e69 unverified no licence file found · pointer only
Benchmarking Pathology Foundation Models: Adaptation Strategies and Scenarios 21 Oct 2024 quiil/benchmarkingpathologyfoundationmodels/data_lib/RandAugment.py e31c4b500a240e69 unverified no licence file found · pointer only
Inversion Circle Interpolation: Diffusion-based Image Augmentation for Data-scarce Classification 29 Aug 2024 scuwyh2000/diff-ii/randaugment.py e31c4b500a240e69 unverified no licence file found · pointer only
Unsupervised Domain Adaption Harnessing Vision-Language Pre-training 5 Aug 2024 Wenlve-Zhou/VLP-UDA/utils/randaugment.py e31c4b500a240e69 unverified MIT (permissive)
OphNet: A Large-Scale Video Benchmark for Ophthalmic Surgical Workflow Understanding 11 Jun 2024 minghu0830/ophnet-benchmark/baselines/task2/backbone/videomaev2/dataset/rand_augment.py 7b2503c99c9447fb ran MIT (permissive)
Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes 9 May 2024 ModelTC/FCPTS/train/randaug.py 7b2503c99c9447fb ran no licence file found · pointer only
Spiking Wavelet Transformer 17 Mar 2024 bic-l/spiking-wavelet-transformer/cifar10-100/aa_snn.py 2d7b973a4b160d73 ran no licence file found · pointer only
EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba 15 Mar 2024 terrypei/efficientvmamba/classification/lib/dataset/augment_ops.py 523681f17bc13539 ran no licence file found · pointer only
Probabilistic Contrastive Learning for Long-Tailed Visual Recognition 11 Mar 2024 leaplabthu/proco/ProCo/randaugment.py e31c4b500a240e69 unverified Apache-2.0 (permissive)
ReViT: Enhancing Vision Transformers Feature Diversity with Attention Residual Connections 17 Feb 2024 adiko1997/revit/dataset/rand_augment.py 7b2503c99c9447fb ran MIT (permissive)
Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket 4 Jan 2024 zk-zhou/spikformer/cifar10/aa_snn.py 2d7b973a4b160d73 ran MIT (permissive)
From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos 9 Dec 2023 FER-LMC/S2D/datasets/rand_augment.py 7b2503c99c9447fb ran Apache-2.0 (permissive)
IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers 7 Oct 2023 hzlsaber/IPMix/cifar.py ca2d43eb1a8c083f ran · our draft was wrong MIT (permissive)
Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation 22 Sep 2023 yue-zhongqi/ICON/icon/randaugment.py e31c4b500a240e69 unverified MIT (permissive)
Prune Spatio-temporal Tokens by Semantic-aware Temporal Accumulation 8 Aug 2023 mark12ding/sta/rand_augment.py 7b2503c99c9447fb ran BSD-2-Clause (permissive)
Video-FocalNets: Spatio-Temporal Focal Modulation for Video Action Recognition 13 Jul 2023 talalwasim/video-focalnets/datasets/rand_augment.py 7b2503c99c9447fb ran no licence file found · pointer only
Reversible Vision Transformers 9 Feb 2023 facebookresearch/mvit/mvit/datasets/rand_augment.py 7b2503c99c9447fb ran Apache-2.0 recorded; this copy not marked cleared · pointer only
Fine-tuned CLIP Models are Efficient Video Learners 6 Dec 2022 muzairkhattak/vifi-clip/datasets/rand_augment.py 7b2503c99c9447fb ran MIT (permissive)
AdaMAE: Adaptive Masking for Efficient Spatiotemporal Learning with Masked Autoencoders 16 Nov 2022 wgcban/adamae/rand_augment.py 7b2503c99c9447fb ran MIT (permissive)
Self-Supervision Can Be a Good Few-Shot Learner 19 Jul 2022 bbbdylan/unisiam/transform/rand_augmentation.py e31c4b500a240e69 unverified MIT (permissive)
ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning 27 Jun 2022 linziyi96/st-adapter/video_dataset/rand_augment.py 7b2503c99c9447fb ran MIT (permissive)
Mugs: A Multi-Granular Self-Supervised Learning Framework 27 Mar 2022 sail-sg/mugs/src/RandAugment.py 7b2503c99c9447fb ran Apache-2.0 (permissive)
Swin Transformer V2: Scaling Up Capacity and Resolution 18 Nov 2021 nku-shengzheliu/PaddlePaddle-Swin-Transformer-V2/auto_augment.py 00da552067622c6f unverified Apache-2.0 (permissive)
Masked Autoencoders Are Scalable Vision Learners 11 Nov 2021 yangyucheng000/mae/src/datasets/auto_augment.py f72f09eb9fd3f148 unverified Apache-2.0 (permissive)
Masked Autoencoders Are Scalable Vision Learners 11 Nov 2021 yongyupei/papers_with_examps/mae/src/process_datasets/auto_augment.py cdd7912370ff7225 unverified Apache-2.0 (permissive)
MEMO: Test Time Robustness via Adaptation and Augmentation 18 Oct 2021 kowshikthopalli/sista/SISTA_DA/image_target_memo.py 137c0aa9944debc9 ran · our draft was wrong no licence file found · pointer only
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation 13 Sep 2021 cdtrans/cdtrans/datasets/autoaugment.py 368f32c4172985b4 unverified MIT (permissive)
RepNAS: Searching for Efficient Re-parameterizing Blocks 8 Sep 2021 bestfleer/RepNAS/utils/auto_augment.py 2d7b973a4b160d73 ran MIT (permissive)
Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain 19 Aug 2021 iCGY96/APR/datasets/APR.py 5615796e020bb66b ran · our draft was wrong MIT (permissive)
Diverse Gaussian Noise Consistency Regularization for Robustness and Uncertainty Calibration 2 Apr 2021 theot1/dign/DiGN.py 0af81fabe08c27e1 ran · our draft was wrong MIT (permissive)
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization 29 Jun 2020 hendrycks/imagenet-r/deepfashion_remix/augmix.py 74de255c18b450ef ran · our draft was wrong MIT (permissive)
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty 5 Dec 2019 google-research/augmix/augment_and_mix.py 5f85c72fd68f99c9 ran · our draft was wrong Apache-2.0 (permissive)
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty 5 Dec 2019 ma7555/Augz/augmix.py ef1702945ac35972 ran · our draft was wrong no licence file found · pointer only
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty 5 Dec 2019 Kaushal28/Bengali-AI/src/dataset.py 57cd2fdb86115db3 ran · our draft was wrong no licence file found · pointer only
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation 16 Nov 2019 moskomule/dda/dda/pil.py 8959fa6a39629fbc unverified MIT (permissive)
RandAugment: Practical automated data augmentation with a reduced search space 30 Sep 2019 lyxxn0414/test-data-generation/auto_augment.py eb627b1078fe24a3 ran fingerprinted no licence file found · pointer only
Graph-Based Global Reasoning Networks 30 Nov 2018 yangyucheng000/glore_res200/src/transform_utils.py 523681f17bc13539 ran Apache-2.0 (permissive)
arXiv:ijcai2025_0115 Gwxer/Hierarchical-Adapter/datasets/rand_augment.py 7b2503c99c9447fb ran MIT (permissive)
arXiv:136950157 kami93/kcenter_video/kcenter_transformer/datasets/autoaugment.py e31c4b500a240e69 unverified Apache-2.0 (permissive)
arXiv:136850478 leo-gb/UMA/ccs_training/models/autoaugment_v2.py 368f32c4172985b4 unverified MIT (permissive)

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".

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