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autopad

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

autopad appears in the code Syntology harvested for 36 papers, as 8 distinct code bodies found in 38 places (a place is one code body under one paper). At least one of them ran in 32 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 autopad 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 5 of the 8 distinct code bodies named autopad; 3 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

5ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
0ran
3unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 15 of the 38 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

36 papers shown of 36, newest first; 38 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; 5 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
Revisiting Adversarial Patch Defenses on Object Detectors: Unified Evaluation, Large-Scale Dataset, and New Insights added by Syntology 2025-08 (from id) Gandolfczjh/APDE/defense/NAPGuard/models/common.py 86db6b7ab1646a7c ran · honoured contract no licence file found · pointer only
U-RWKV: Lightweight medical image segmentation with direction-adaptive RWKV 15 Jul 2025 hbyecoding/u-rwkv/models/cmunext/cmunext_rwkv_test_bk1226.py ea5a7ec9e9b7cd6c unverified MIT (permissive)
Reviving Cultural Heritage: A Novel Approach for Comprehensive Historical Document Restoration 7 Jul 2025 SCUT-DLVCLab/AutoHDR/models/common.py 988a3c854b1b13d0 ran · honoured contract no licence file found · pointer only
DEAL: Data-Efficient Adversarial Learning for High-Quality Infrared Imaging 2 Mar 2025 LiuZhu-CV/DEAL/DEAL/models/model_ne.py 86db6b7ab1646a7c ran · honoured contract no licence file found · pointer only
OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving 19 Dec 2024 taco-group/openemma/openemma/YOLO3D/models/common.py 988a3c854b1b13d0 ran · honoured contract Apache-2.0 (permissive)
DEIM: DETR with Improved Matching for Fast Convergence 5 Dec 2024 shihuahuang95/deim/engine/backbone/csp_darknet.py 988a3c854b1b13d0 ran · honoured contract no licence file found · pointer only
Masala-CHAI: A Large-Scale SPICE Netlist Dataset for Analog Circuits by Harnessing AI 2024-11 (from id) jitendra-bhandari/auto-spice/models/common.py 77aee8b50f981306 unverified no licence file found · pointer only
PK-YOLO: Pretrained Knowledge Guided YOLO for Brain Tumor Detection in Multiplanar MRI Slices 29 Oct 2024 mkang315/PK-YOLO/models/common.py 86db6b7ab1646a7c ran · honoured contract GPL-3.0 (copyleft) · pointer only
CFMW: Cross-modality Fusion Mamba for Multispectral Object Detection under Adverse Weather Conditions 25 Apr 2024 lhy-zjut/cfmw/models/common.py 988a3c854b1b13d0 ran · honoured contract AGPL-3.0 (copyleft) · pointer only
Privacy-Preserving Autoencoder for Collaborative Object Detection 29 Feb 2024 bardia-az/ppa-code/models/common.py 988a3c854b1b13d0 ran · honoured contract Apache-2.0 (permissive)
YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information 21 Feb 2024 ultralytics/ultralytics/ultralytics/nn/modules/block.py 11ea59c9308130b2 ran · honoured contract AGPL-3.0 (copyleft) · pointer only
YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information 21 Feb 2024 WongKinYiu/yolov9/models/common.py 86db6b7ab1646a7c ran · honoured contract GPL-3.0 (copyleft) · pointer only
Exploiting Polarized Material Cues for Robust Car Detection 5 Jan 2024 identical code first harvested elsewhere 988a3c854b1b13d0 ran · honoured contract licence of this copy not recorded
ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation 11 Dec 2023 mkang315/asf-yolo/models/common.py 86db6b7ab1646a7c ran · honoured contract AGPL-3.0 (copyleft) · pointer only
AMSP-UOD: When Vortex Convolution and Stochastic Perturbation Meet Underwater Object Detection 23 Aug 2023 zhoujingchun03/amsp-uod/models/baseLayer.py 86db6b7ab1646a7c ran · honoured contract no licence file found · pointer only
Unified Adversarial Patch for Cross-modal Attacks in the Physical World 15 Jul 2023 aries-iai/cross-modal_patch_attack/yolov3/models/common.py 988a3c854b1b13d0 ran · honoured contract MIT (permissive)
YOLOv6 v3.0: A Full-Scale Reloading 13 Jan 2023 identical code first harvested elsewhere 988a3c854b1b13d0 ran · honoured contract licence of this copy not recorded
Benchmarking Adversarial Patch Against Aerial Detection 30 Oct 2022 jiaweilian/ap-pa/models/common.py 988a3c854b1b13d0 ran · honoured contract Apache-2.0 (permissive)
YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications 7 Sep 2022 yang-0201/YOLOv6_pro/models/yolov6.py 988a3c854b1b13d0 ran · honoured contract GPL-3.0 (copyleft) · pointer only
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors 6 Jul 2022 kadirnar/yolov7-pip/yolov7/models/common.py 988a3c854b1b13d0 ran · honoured contract MIT (permissive)
BoT-SORT: Robust Associations Multi-Pedestrian Tracking 29 Jun 2022 niraharon/bot-sort/yolov7/models/common.py 988a3c854b1b13d0 ran · honoured contract MIT (permissive)
SeqTR: A Simple yet Universal Network for Visual Grounding 30 Mar 2022 luogen1996/simrec/simrec/layers/blocks.py 988a3c854b1b13d0 ran · honoured contract Apache-2.0 (permissive)
LAFITE: Towards Language-Free Training for Text-to-Image Generation 27 Nov 2021 oxygenlu/ratlip/code/models/RATLIP.py 988a3c854b1b13d0 ran · honoured contract MIT (permissive)
DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentation 31 May 2020 Latterlig96/DCUnet/core/utils.py 988a3c854b1b13d0 ran · honoured contract MIT (permissive)
YOLOv4: Optimal Speed and Accuracy of Object Detection 23 Apr 2020 GuoQuanhao/YOLOv4-Paddle/models/common.py 988a3c854b1b13d0 ran · honoured contract MIT (permissive)
YOLOv4: Optimal Speed and Accuracy of Object Detection 23 Apr 2020 Yuzi0123/MindSpore_Yolov5/network/common.py 86db6b7ab1646a7c ran · honoured contract MIT (permissive)
Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC) 9 Feb 2019 Woodman718/FixCaps/Module/model410.py 988a3c854b1b13d0 ran · honoured contract MIT (permissive)
YOLOv3: An Incremental Improvement 8 Apr 2018 yuedongli1/yolov3_mindspore/network/common.py 988a3c854b1b13d0 ran · honoured contract MIT (permissive)
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications 17 Apr 2017 Deci-AI/super-gradients/src/super_gradients/modules/conv_bn_act_block.py 3679480e08fecc84 ran · honoured contract Apache-2.0 (permissive)
Simple Online and Realtime Tracking with a Deep Association Metric 21 Mar 2017 pvtien96/D2DP/models/common.py 988a3c854b1b13d0 ran · honoured contract Apache-2.0 (permissive)
Multispectral Deep Neural Networks for Pedestrian Detection 8 Nov 2016 xuez-phd/tfdet/yolov5-master/models/common.py 86db6b7ab1646a7c ran · honoured contract Apache-2.0 (permissive)
Deep Residual Learning for Image Recognition 10 Dec 2015 ultralytics/yolov5/models/common.py c66ee16c44e505a8 ran · honoured contract AGPL-3.0 (copyleft) · pointer only
Rich feature hierarchies for accurate object detection and semantic segmentation 11 Nov 2013 jiangbestone/DetectRccn/models/common.py 988a3c854b1b13d0 ran · honoured contract MIT (permissive)
arXiv:aaai_27996 hukefy/DALDet/additions/models/common.py a09c1775cd9fe501 unverified Apache-2.0 (permissive)
arXiv:aaai_26777 weihui1308/HOTCOLDBlock/victim_detector/models/common.py a09c1775cd9fe501 unverified Apache-2.0 (permissive)
arXiv:Yu_Revisiting_Counterfactual_Problems_in_Referring_Expression_Comprehension_CVPR_2024_paper Glacier0012/CREC/crec/layers/blocks.py 988a3c854b1b13d0 ran · honoured contract Apache-2.0 (permissive)
arXiv:Wang_Cant_Slow_Me_Down_Learning_Robust_and_Hardware-Adaptive_Object_Detectors_CVPR_2025_paper Hill-Wu-1998/underload/robust_pkgs/ultralytics-yolov5-robust-0.0.1/yolov5/models/common.py 988a3c854b1b13d0 ran · honoured contract Apache-2.0 (permissive)
arXiv:Gao_AsyFOD_An_Asymmetric_Adaptation_Paradigm_for_Few-Shot_Domain_Adaptive_Object_CVPR_2023_paper Hlings/AsyFOD/models/common.py 988a3c854b1b13d0 ran · honoured contract 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".

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections