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translate_x_rel

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

translate_x_rel appears in the code Syntology harvested for 27 papers, as 7 distinct code bodies found in 28 places (a place is one code body under one paper). At least one of them ran in 21 of the papers; 0 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 translate_x_rel 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 3 of the 7 distinct code bodies named translate_x_rel; 4 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
3ran
4unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 7 of the 28 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

27 papers shown of 27, newest first; 28 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 a4b471197204b414 ran no licence file found · pointer only
Benchmarking Pathology Foundation Models: Adaptation Strategies and Scenarios 21 Oct 2024 quiil/benchmarkingpathologyfoundationmodels/data_lib/RandAugment.py a4b471197204b414 ran 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 a4b471197204b414 ran no licence file found · pointer only
Unsupervised Domain Adaption Harnessing Vision-Language Pre-training 5 Aug 2024 Wenlve-Zhou/VLP-UDA/utils/randaugment.py a4b471197204b414 ran 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 323759f906fbb394 ran MIT (permissive)
Spiking Wavelet Transformer 17 Mar 2024 bic-l/spiking-wavelet-transformer/cifar10-100/aa_snn.py 61f2a3e08a11e1f5 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 f38706e32849458d ran no licence file found · pointer only
Probabilistic Contrastive Learning for Long-Tailed Visual Recognition 11 Mar 2024 leaplabthu/proco/ProCo/randaugment.py a4b471197204b414 ran Apache-2.0 (permissive)
ReViT: Enhancing Vision Transformers Feature Diversity with Attention Residual Connections 17 Feb 2024 adiko1997/revit/dataset/rand_augment.py 323759f906fbb394 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 61f2a3e08a11e1f5 unverified 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 323759f906fbb394 ran Apache-2.0 (permissive)
Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation 22 Sep 2023 yue-zhongqi/ICON/icon/randaugment.py a4b471197204b414 ran MIT (permissive)
Prune Spatio-temporal Tokens by Semantic-aware Temporal Accumulation 8 Aug 2023 mark12ding/sta/rand_augment.py 323759f906fbb394 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 323759f906fbb394 ran no licence file found · pointer only
Reversible Vision Transformers 9 Feb 2023 facebookresearch/mvit/mvit/datasets/rand_augment.py 323759f906fbb394 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 323759f906fbb394 ran MIT (permissive)
AdaMAE: Adaptive Masking for Efficient Spatiotemporal Learning with Masked Autoencoders 16 Nov 2022 wgcban/adamae/rand_augment.py 323759f906fbb394 ran MIT (permissive)
Self-Supervision Can Be a Good Few-Shot Learner 19 Jul 2022 bbbdylan/unisiam/transform/rand_augmentation.py a4b471197204b414 ran MIT (permissive)
ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning 27 Jun 2022 linziyi96/st-adapter/video_dataset/rand_augment.py 323759f906fbb394 ran MIT (permissive)
Mugs: A Multi-Granular Self-Supervised Learning Framework 27 Mar 2022 sail-sg/mugs/src/RandAugment.py 323759f906fbb394 ran Apache-2.0 (permissive)
Masked Autoencoders Are Scalable Vision Learners 11 Nov 2021 yangyucheng000/mae/src/datasets/auto_augment.py f3b161d964735796 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 1644b5d70651bbcf unverified Apache-2.0 (permissive)
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation 13 Sep 2021 cdtrans/cdtrans/datasets/autoaugment.py aa897f695e05da40 unverified MIT (permissive)
RepNAS: Searching for Efficient Re-parameterizing Blocks 8 Sep 2021 bestfleer/RepNAS/utils/auto_augment.py 61f2a3e08a11e1f5 unverified MIT (permissive)
Graph-Based Global Reasoning Networks 30 Nov 2018 yangyucheng000/glore_res200/src/transform_utils.py f38706e32849458d ran Apache-2.0 (permissive)
arXiv:ijcai2025_0115 Gwxer/Hierarchical-Adapter/datasets/rand_augment.py 323759f906fbb394 ran MIT (permissive)
arXiv:136950157 kami93/kcenter_video/kcenter_transformer/datasets/autoaugment.py a4b471197204b414 ran Apache-2.0 (permissive)
arXiv:136850478 leo-gb/UMA/ccs_training/models/autoaugment_v2.py aa897f695e05da40 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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