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round_repeats

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

round_repeats appears in the code Syntology harvested for 39 papers, as 17 distinct code bodies found in 47 places (a place is one code body under one paper). At least one of them ran in 33 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 round_repeats 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 11 of the 17 distinct code bodies named round_repeats; 6 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

9ran · honoured contract
0ran · violated contract
1ran · our draft was wrong
0ran · fixture could not drive it
1ran
6unverified
5fingerprinted

Licence is a property of each copy, so it is counted per place: 14 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

39 papers shown of 39, 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 1 papers added by Syntology. 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
When AUC Misleads: Polarization-Aware Evaluation of Deepfake Detectors under Domain Shift added by Syntology 2026-06 (from id) megvii-research/CADDM/backbones/efficientnet_pytorch/utils.py 4d8e794b593d34a0 ran · honoured contract Apache-2.0 (permissive)
Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection 4 Mar 2024 qingyuliu/exposing-the-deception/models/MI_Net.py dbc0ca08d119a5a0 ran · our draft was wrong Apache-2.0 (permissive)
GenFace: A Large-Scale Fine-Grained Face Forgery Benchmark and Cross Appearance-Edge Learning 3 Feb 2024 jenine-321/genface/model/efficient_net/efficientnet_pytorch/utils.py dbc0ca08d119a5a0 ran · our draft was wrong no licence file found · pointer only
ZoomNeXt: A Unified Collaborative Pyramid Network for Camouflaged Object Detection 31 Oct 2023 lartpang/zoomnext/methods/backbone/efficientnet_utils.py dbc0ca08d119a5a0 ran · our draft was wrong no licence file found · pointer only
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer 11 Oct 2023 ZackZikaiXiao/FedGraB/model/effutil.py 70f48a3907311f52 ran no licence file found · pointer only
Fine-Grained Cross-View Geo-Localization Using a Correlation-Aware Homography Estimator 31 Aug 2023 xlwangdev/hc-net/models/efficientnet_pytorch/utils.py dbc0ca08d119a5a0 ran · our draft was wrong no licence file found · pointer only
SILT: Shadow-aware Iterative Label Tuning for Learning to Detect Shadows from Noisy Labels 23 Aug 2023 Cralence/SILT/model/backbone/efficientnet_pytorch/utils.py dbc0ca08d119a5a0 ran · our draft was wrong no licence file found · pointer only
Manifold-Aware Self-Training for Unsupervised Domain Adaptation on Regressing 6D Object Pose 18 May 2023 Gorilla-Lab-SCUT/MAST/MAST/models/efficientnet_utils.py 4d8e794b593d34a0 ran · honoured contract MIT (permissive)
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_v2.py 6cc796a8212b5586 unverified Apache-2.0 (permissive)
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification 17 Jun 2022 cambridge-mlg/fit/src/efficientnet_utils.py dbc0ca08d119a5a0 ran · our draft was wrong MIT (permissive)
Knowledge Distillation as Efficient Pre-training: Faster Convergence, Higher Data-efficiency, and Better Transferability 10 Mar 2022 CVMI-Lab/KDEP/src/efficientnet_utils.py dbc0ca08d119a5a0 ran · our draft was wrong Apache-2.0 (permissive)
AutoBalance: Optimized Loss Functions for Imbalanced Data 4 Jan 2022 ucr-optml/autobalance/models/utils.py 4d8e794b593d34a0 ran · honoured contract MIT (permissive)
Projected GANs Converge Faster 1 Nov 2021 dome272/ProjectedGAN-pytorch/projected_gan.py b5099ac2f4a497ef ran · honoured contract fingerprinted MIT (permissive)
Open-Set Recognition: a Good Closed-Set Classifier is All You Need? 12 Oct 2021 sgvaze/osr_closed_set_all_you_need/models/miscel_utils.py dbc0ca08d119a5a0 ran · our draft was wrong MIT (permissive)
Combining EfficientNet and Vision Transformers for Video Deepfake Detection 6 Jul 2021 davide-coccomini/Combining-EfficientNet-and-Vision-Transformers-for-Video-Deepfake-Detection/cross-efficient-vit/efficient_net/efficientnet_pytorch/utils.py dbc0ca08d119a5a0 ran · our draft was wrong MIT (permissive)
CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation 6 Jul 2021 alsgkals2/CoReD_Released/utils.py 70f48a3907311f52 ran MIT (permissive)
Memory Efficient Meta-Learning with Large Images 2 Jul 2021 cambridge-mlg/LITE/src/efficientnet_utils.py dbc0ca08d119a5a0 ran · our draft was wrong MIT (permissive)
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning 7 Jun 2021 thlarsen13/thlarsen_uncertainty_models/uncertainty_baselines/models/efficientnet.py e316074dac020280 unverified Apache-2.0 (permissive)
Learning from Ambiguous Labels for Lung Nodule Malignancy Prediction 23 Apr 2021 Merrical/DAR/EfficientNet_2d/utils.py 4d8e794b593d34a0 ran · honoured contract MIT (permissive)
M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection 20 Apr 2021 wangjk666/PyDeepFakeDet/PyDeepFakeDet/models/efficientnet.py f93cb693ac8bb537 ran · honoured contract MIT (permissive)
EfficientNetV2: Smaller Models and Faster Training 1 Apr 2021 seermer/TensorFlow2-EfficientNetV2/efficientnetV2.py 1a9d7e65e0a9fbc9 ran · honoured contract fingerprinted MIT (permissive)
EfficientNetV2: Smaller Models and Faster Training 1 Apr 2021 Klassikcat/project-NEXTLab-CNN-EfficientNet/EfficientNet_codestates/model/model.py f93cb693ac8bb537 ran · honoured contract no licence file found · pointer only
EfficientNetV2: Smaller Models and Faster Training 1 Apr 2021 abhuse/pytorch-efficientnet/efficientnet_v2.py 167f9f74323c7278 ran · honoured contract fingerprinted MIT (permissive)
Multi-attentional Deepfake Detection 3 Mar 2021 yoctta/multiple-attention/models/MAT.py 4d8e794b593d34a0 ran · honoured contract no licence file found · pointer only
Sharpness-Aware Minimization for Efficiently Improving Generalization 3 Oct 2020 google-research/sam/sam_jax/efficientnet/efficientnet.py 61a40ee8921487b9 unverified Apache-2.0 (permissive)
FSD50K: An Open Dataset of Human-Labeled Sound Events 1 Oct 2020 SarthakYadav/GISE-51-pytorch/src/models/efficientnet_pytorch/utils.py dbc0ca08d119a5a0 ran · our draft was wrong MIT (permissive)
BOP Challenge 2020 on 6D Object Localization 15 Sep 2020 azad96/cosypose-custom/cosypose/models/efficientnet_utils.py 4d8e794b593d34a0 ran · honoured contract MIT (permissive)
CosyPose: Consistent multi-view multi-object 6D pose estimation 19 Aug 2020 princeton-vl/coupled-iterative-refinement/pose_models/efficientnet_utils.py 4d8e794b593d34a0 ran · honoured contract MIT (permissive)
T-GD: Transferable GAN-generated Images Detection Framework 10 Aug 2020 cutz-j/T-GD/models/utils.py 4d8e794b593d34a0 ran · honoured contract MIT (permissive)
X3D: Expanding Architectures for Efficient Video Recognition 9 Apr 2020 Chianugoogidi/X3D-tf/utils.py 4ed34e164b9d3a9f unverified MIT (permissive)
Designing Network Design Spaces 30 Mar 2020 ZHANGHeng19931123/MutualGuide/models/backbone/efficientnet_backbone.py f93cb693ac8bb537 ran · honoured contract MIT (permissive)
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data 13 Mar 2020 BingLiHanShuang/AutoGluon_IntegrateSimpleFeedforward/autogluon/model_zoo/models/utils.py 150b610493a774c4 unverified Apache-2.0 (permissive)
YOLACT++: Better Real-time Instance Segmentation 3 Dec 2019 SpaceView/Yolact_EfficientNet/efficientnet/utils.py 4d8e794b593d34a0 ran · honoured contract MIT (permissive)
YOLACT++: Better Real-time Instance Segmentation 3 Dec 2019 kaylode/Clothes-Segmentation/efficient_utils.py dbc0ca08d119a5a0 ran · our draft was wrong MIT (permissive)
Leveraging Procedural Generation to Benchmark Reinforcement Learning 3 Dec 2019 rgilman33/carlita/efficientnet_utils.py dbc0ca08d119a5a0 ran · our draft was wrong MIT recorded; this copy not marked cleared · pointer only
Soft Anchor-Point Object Detection 27 Nov 2019 xuannianz/SAPD/efficientnet.py 6cc796a8212b5586 unverified Apache-2.0 (permissive)
GhostNet: More Features from Cheap Operations 27 Nov 2019 identical code first harvested elsewhere 1a9d7e65e0a9fbc9 ran · honoured contract fingerprinted licence of this copy not recorded
EfficientDet: Scalable and Efficient Object Detection 20 Nov 2019 GuoQuanhao/EfficientDet-Paddle/efficientnet/utils.py 4d8e794b593d34a0 ran · honoured contract MIT (permissive)
EfficientDet: Scalable and Efficient Object Detection 20 Nov 2019 xuannianz/EfficientDet/efficientnet.py 6cc796a8212b5586 unverified Apache-2.0 (permissive)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 isaachaw/GrabCarRecognition/efficientnet/model.py a02458cc5b951e63 ran · honoured contract GPL-3.0 (copyleft) · pointer only
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 abhuse/pytorch-efficientnet/efficientnet.py 0bacadac82be1cf1 ran · honoured contract fingerprinted MIT (permissive)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 tsing-cv/EfficientNet-tensorflow-eager/model.py 32213b389c413189 ran · honoured contract no licence file found · pointer only
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 qubvel/efficientnet/efficientnet/model.py 6cc796a8212b5586 unverified Apache-2.0 recorded; this copy not marked cleared · pointer only
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 titu1994/keras-efficientnets/keras_efficientnets/efficientnet.py 93d5e9bbed1bbac6 unverified MIT (permissive)
Bag of Tricks for Image Classification with Convolutional Neural Networks 4 Dec 2018 identical code first harvested elsewhere 1a9d7e65e0a9fbc9 ran · honoured contract fingerprinted licence of this copy not recorded
Recalibrating Fully Convolutional Networks with Spatial and Channel 'Squeeze & Excitation' Blocks 23 Aug 2018 qubvel/segmentation_models.pytorch/segmentation_models_pytorch/encoders/_efficientnet.py dbc0ca08d119a5a0 ran · our draft was wrong MIT (permissive)
Deep clustering: Discriminative embeddings for segmentation and separation 18 Aug 2015 tsian077/Deep_Clustering_EfficientNet/DeWave/model.py 30fc65e29d79bc63 ran · honoured contract 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".

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