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MBConvBlock

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

MBConvBlock appears in the code Syntology harvested for 10 papers, as 21 distinct code bodies found in 21 places (a place is one code body under one paper). At least one of them ran in 7 of the papers; 6 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 MBConvBlock 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 MBConvBlock; 9 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
1ran · our draft was wrong
0ran · fixture could not drive it
11ran
9unverified
6fingerprinted

Licence is a property of each copy, so it is counted per place: 9 of the 21 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

10 papers shown of 10, newest first; 21 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
Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection 4 Mar 2024 qingyuliu/exposing-the-deception/models/MI_Net.py 22224e6f538dca75 ran · metamorphic tier: deterministic fingerprinted Apache-2.0 (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 6bd8585a9f22e0d2 unverified Apache-2.0 (permissive)
Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation 3 May 2022 mit-han-lab/litepose/lib/models/pose_efficient_hrnet.py e966f3ae5dde908b ran · metamorphic tier: invariant fingerprinted MIT (permissive)
MaxViT: Multi-Axis Vision Transformer 4 Apr 2022 google-research/maxvit/maxvit/models/maxvit.py 2d7a9595c2215efd unverified Apache-2.0 (permissive)
Optimization Planning for 3D ConvNets 11 Jan 2022 zhaofanqiu/optimization-planning-for-3d-convnets/model/seq_p3d_eftnet.py 23f2cb856678d5d4 unverified licence not identified · pointer only
Projected GANs Converge Faster 1 Nov 2021 dome272/ProjectedGAN-pytorch/projected_gan.py d65e8029380ee87d ran · metamorphic tier: deterministic fingerprinted MIT (permissive)
EfficientNetV2: Smaller Models and Faster Training 1 Apr 2021 Klassikcat/project-NEXTLab-CNN-EfficientNet/EfficientNet_codestates/model/model.py cb2b257652e0c5cc ran · our draft was wrong no licence file found · pointer only
Model-based 3D Hand Reconstruction via Self-Supervised Learning 22 Mar 2021 TerenceCYJ/S2HAND/efficientnet_pt/model.py 45905dfc075fd4b9 ran no licence file found · pointer only
Multi-attentional Deepfake Detection 3 Mar 2021 yoctta/multiple-attention/models/MAT.py 12770455a6977457 ran · metamorphic tier: deterministic no licence file found · pointer only
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 chrisqqq123/FA-Dist-EfficientNet/models/efficientnet.py 6eb3c2113f675e0d ran · metamorphic tier: deterministic fingerprinted MIT (permissive)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 isaachaw/GrabCarRecognition/efficientnet/model.py 20b2eb990021c72b ran · metamorphic tier: deterministic GPL-3.0 (copyleft) · pointer only
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 AmirmohammadRostami/KeywordsSpotting-EfficientNet-A0/utils/efficientnet_pytorch/model.py 04c2b7413de3c583 ran fingerprinted MIT (permissive)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 github-luffy/PFLD_68points_Pytorch/efficientnet/model.py 45c9c18b06c8bcb5 ran no licence file found · pointer only
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 Mayurji/Image-Classification-PyTorch/EfficientNet.py 4ec0cd472dab11e6 ran fingerprinted GPL-3.0 (copyleft) · pointer only
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 rohitgr7/tvmodels/tvmodels/models/blocks/effnet_blocks.py e0d1e58cc21f79d6 ran MIT (permissive)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 facebookresearch/ClassyVision/classy_vision/models/efficientnet.py 59722dac41b7de0c unverified MIT (permissive)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 abhuse/pytorch-efficientnet/efficientnet.py d9d45fe93ed744ce unverified MIT (permissive)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 tsing-cv/EfficientNet-tensorflow-eager/model.py 1138d11e9960eaac unverified no licence file found · pointer only
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 lukemelas/EfficientNet-PyTorch/efficientnet_pytorch/model.py 74e34b309f1b102a unverified Apache-2.0 (permissive)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 gouthamvgk/coreml_conversion_hub/pytorch/detection/efficientDet/Yet-Another-EfficientDet-Pytorch/efficientnet/model.py 8d56be7c0c811019 unverified no licence file found · pointer only
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 morganmcg1/stanford-cars/MEfficientNet_PyTorch/efficientnet_pytorch/model.py 1eb95486a498bc00 unverified Apache-2.0 (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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