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shear_x

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

shear_x appears in the code Syntology harvested for 43 papers, as 21 distinct code bodies found in 47 places (a place is one code body under one paper). At least one of them ran in 26 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_x 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 21 distinct code bodies named shear_x; 9 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
1ran · fixture could not drive it
3ran
9unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 15 of the 47 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

43 papers shown of 43, newest first; 47 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; 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 7b4e3d0bd192b677 unverified no licence file found · pointer only
Cooperative Pseudo Labeling for Unsupervised Federated Classification added by Syntology 2025-10 (from id) krumpguo/FedCoPL/methods/data_aug_utils.py 53613a740588d619 ran · fixture could not drive it no licence file found · pointer only
Benchmarking Pathology Foundation Models: Adaptation Strategies and Scenarios 21 Oct 2024 quiil/benchmarkingpathologyfoundationmodels/data_lib/RandAugment.py 7b4e3d0bd192b677 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 7b4e3d0bd192b677 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 7b4e3d0bd192b677 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 e866e1196986f728 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 e866e1196986f728 ran no licence file found · pointer only
Spiking Wavelet Transformer 17 Mar 2024 bic-l/spiking-wavelet-transformer/cifar10-100/aa_snn.py b31e84df5541213a unverified 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 8eaf53b48155177c ran no licence file found · pointer only
Probabilistic Contrastive Learning for Long-Tailed Visual Recognition 11 Mar 2024 leaplabthu/proco/ProCo/randaugment.py 7b4e3d0bd192b677 unverified Apache-2.0 (permissive)
ReViT: Enhancing Vision Transformers Feature Diversity with Attention Residual Connections 17 Feb 2024 adiko1997/revit/dataset/rand_augment.py e866e1196986f728 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 b31e84df5541213a unverified MIT (permissive)
CR-SAM: Curvature Regularized Sharpness-Aware Minimization 21 Dec 2023 trustaiot/cr-sam/utils/autoaugment.py 53613a740588d619 ran · fixture could not drive it no licence file found · pointer only
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 e866e1196986f728 ran Apache-2.0 (permissive)
Typhoon Intensity Prediction with Vision Transformer 28 Nov 2023 chen-huanxin/Tint/data_augmentation/auto_augment.py 53613a740588d619 ran · fixture could not drive it no licence file found · pointer only
IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers 7 Oct 2023 hzlsaber/IPMix/cifar.py 7dbf6f8a2088e9be 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 7b4e3d0bd192b677 unverified MIT (permissive)
Prune Spatio-temporal Tokens by Semantic-aware Temporal Accumulation 8 Aug 2023 mark12ding/sta/rand_augment.py e866e1196986f728 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 e866e1196986f728 ran no licence file found · pointer only
Reversible Vision Transformers 9 Feb 2023 facebookresearch/mvit/mvit/datasets/rand_augment.py e866e1196986f728 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 e866e1196986f728 ran MIT (permissive)
AdaMAE: Adaptive Masking for Efficient Spatiotemporal Learning with Masked Autoencoders 16 Nov 2022 wgcban/adamae/rand_augment.py e866e1196986f728 ran MIT (permissive)
Self-Supervision Can Be a Good Few-Shot Learner 19 Jul 2022 bbbdylan/unisiam/transform/rand_augmentation.py 7b4e3d0bd192b677 unverified MIT (permissive)
ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning 27 Jun 2022 linziyi96/st-adapter/video_dataset/rand_augment.py e866e1196986f728 ran MIT (permissive)
Mugs: A Multi-Granular Self-Supervised Learning Framework 27 Mar 2022 sail-sg/mugs/src/RandAugment.py e866e1196986f728 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 e0254103b7a7465f unverified Apache-2.0 (permissive)
Masked Autoencoders Are Scalable Vision Learners 11 Nov 2021 yangyucheng000/mae/src/datasets/auto_augment.py 836abfc1dec21f54 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 328334d15e09e000 unverified Apache-2.0 (permissive)
MEMO: Test Time Robustness via Adaptation and Augmentation 18 Oct 2021 kowshikthopalli/sista/SISTA_DA/image_target_memo.py 4e80aa228ea65fb6 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 ec44d1cea891fdb3 unverified MIT (permissive)
RepNAS: Searching for Efficient Re-parameterizing Blocks 8 Sep 2021 bestfleer/RepNAS/utils/auto_augment.py b31e84df5541213a unverified MIT (permissive)
Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain 19 Aug 2021 iCGY96/APR/datasets/APR.py 417bb83cee1eb445 ran · our draft was wrong MIT (permissive)
Diverse Gaussian Noise Consistency Regularization for Robustness and Uncertainty Calibration 2 Apr 2021 theot1/dign/DiGN.py 8baad92985baea5d 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 8b301c76d5b96b5f 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 1020c7cab8402b62 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 0aa9d6add4980494 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 6e3bb2bc13b0e703 ran · our draft was wrong no licence file found · pointer only
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation 16 Nov 2019 moskomule/dda/dda/functional.py 90f7118023305b3b unverified MIT (permissive)
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation 16 Nov 2019 moskomule/dda/dda/pil.py 1bcc85675f7606d4 unverified MIT (permissive)
RandAugment: Practical automated data augmentation with a reduced search space 30 Sep 2019 lyxxn0414/test-data-generation/auto_augment.py 7fad25ebc151a21a ran fingerprinted no licence file found · pointer only
Once-for-All: Train One Network and Specialize it for Efficient Deployment 26 Aug 2019 pprp/ofa-cifar/ofa/imagenet_classification/data_providers/cifar10.py 3c5071b8a3d0e038 unverified MIT (permissive)
All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification 13 Mar 2019 hikvision-research/SparseShiftLayer/models/auto_augment.py 53613a740588d619 ran · fixture could not drive it Apache-2.0 (permissive)
Graph-Based Global Reasoning Networks 30 Nov 2018 yangyucheng000/glore_res200/src/transform_utils.py 8eaf53b48155177c ran Apache-2.0 (permissive)
AutoAugment: Learning Augmentation Policies from Data 24 May 2018 4uiiurz1/pytorch-auto-augment/auto_augment.py 53613a740588d619 ran · fixture could not drive it MIT (permissive)
arXiv:ijcai2025_0115 Gwxer/Hierarchical-Adapter/datasets/rand_augment.py e866e1196986f728 ran MIT (permissive)
arXiv:136950157 kami93/kcenter_video/kcenter_transformer/datasets/autoaugment.py 7b4e3d0bd192b677 unverified Apache-2.0 (permissive)
arXiv:136850478 leo-gb/UMA/ccs_training/models/autoaugment_v2.py ec44d1cea891fdb3 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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