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lr_poly

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

lr_poly appears in the code Syntology harvested for 25 papers, as 6 distinct code bodies found in 25 places (a place is one code body under one paper). At least one of them ran in 25 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 lr_poly 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 6 of the 6 distinct code bodies named lr_poly; 0 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
1ran
0unverified
6fingerprinted

Licence is a property of each copy, so it is counted per place: 14 of the 25 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

25 papers shown of 25, newest first; 25 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; 1 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
Density-guided Translator Boosts Synthetic-to-Real Unsupervised Domain Adaptive Segmentation of 3D Point Clouds 27 Mar 2024 yuan-zm/DGT-ST/network/lr_adjust.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted Apache-2.0 (permissive)
Learning without Exact Guidance: Updating Large-scale High-resolution Land Cover Maps from Low-resolution Historical Labels 5 Mar 2024 lizhuohong/segland/ft_pop.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted MIT (permissive)
Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection 21 Dec 2023 identical code first harvested elsewhere b3b7c1c716f4ca66 ran · honoured contract fingerprinted licence of this copy not recorded
CMDA: Cross-Modality Domain Adaptation for Nighttime Semantic Segmentation 29 Jul 2023 XiaRho/CMDA/utils/utils.py a8ad52a812530368 ran fingerprinted no licence file found · pointer only
Online Domain Adaptation for Semantic Segmentation in Ever-Changing Conditions 21 Jul 2022 theo2021/OnDA/framework/domain_adaptation/methods/prototypes.py 9fec89dab050cb13 ran · honoured contract fingerprinted GPL-2.0 (copyleft) · pointer only
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank 27 Apr 2021 Shathe/SemiSeg-Contrastive/trainSSL.py 1b0ce6e9e98a57de ran · honoured contract fingerprinted Apache-2.0 (permissive)
Improving One-stage Visual Grounding by Recursive Sub-query Construction 3 Aug 2020 zyang-ur/ReSC/model/loss.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted MIT (permissive)
DACS: Domain Adaptation via Cross-domain Mixed Sampling 17 Jul 2020 identical code first harvested elsewhere b3b7c1c716f4ca66 ran · honoured contract fingerprinted licence of this copy not recorded
ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning 15 Jul 2020 WilhelmT/ClassMix/trainSSL.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted MIT (permissive)
Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation 13 Apr 2020 identical code first harvested elsewhere b3b7c1c716f4ca66 ran · honoured contract fingerprinted licence of this copy not recorded
Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation 18 Mar 2020 SHI-Labs/Unsupervised-Domain-Adaptation-with-Differential-Treatment/train_sim.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted no licence file found · pointer only
Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation 2 Mar 2020 identical code first harvested elsewhere b3b7c1c716f4ca66 ran · honoured contract fingerprinted licence of this copy not recorded
Saliency Guided Self-attention Network for Weakly and Semi-supervised Semantic Segmentation 12 Oct 2019 identical code first harvested elsewhere b3b7c1c716f4ca66 ran · honoured contract fingerprinted licence of this copy not recorded
A Fast and Accurate One-Stage Approach to Visual Grounding 18 Aug 2019 zyang-ur/onestage_grounding/train_yolo.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted MIT (permissive)
Semi-Supervised Semantic Segmentation with High- and Low-level Consistency 15 Aug 2019 identical code first harvested elsewhere b3b7c1c716f4ca66 ran · honoured contract fingerprinted licence of this copy not recorded
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision 4 Jun 2019 fregu856/evaluating_bdl/segmentation/ensembling_train_syn.py b91a29dacf5ca1a2 ran · honoured contract fingerprinted MIT (permissive)
Domain Adaptation for Structured Output via Discriminative Patch Representations 16 Jan 2019 wasidennis/AdaptSegNet/pytorch_0.4/train_gta2cityscapes_multi.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted no licence file found · pointer only
UPSNet: A Unified Panoptic Segmentation Network 12 Jan 2019 uber-research/UPSNet/upsnet/upsnet_end2end_train.py 93a18ae852753bae ran · honoured contract fingerprinted licence not identified · pointer only
Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation 25 Sep 2018 RoyalVane/CLAN/CLAN_train.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted MIT (permissive)
Learning to Adapt Structured Output Space for Semantic Segmentation 28 Feb 2018 lym29/DASeg/train_gta2cityscapes_multi.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted no licence file found · pointer only
No More Discrimination: Cross City Adaptation of Road Scene Segmenters 27 Apr 2017 identical code first harvested elsewhere b3b7c1c716f4ca66 ran · honoured contract fingerprinted licence of this copy not recorded
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results 6 Mar 2017 identical code first harvested elsewhere b3b7c1c716f4ca66 ran · honoured contract fingerprinted licence of this copy not recorded
Joint 2D-3D-Semantic Data for Indoor Scene Understanding 3 Feb 2017 jamycheung/trans4pass/adaptations/train_mpa.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted Apache-2.0 (permissive)
Learning Video Object Segmentation from Static Images 8 Dec 2016 omkar13/MaskTrack/training/utility_functions.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted MIT (permissive)
arXiv:136940019 ETHRuiGong/TADA/trainTACS_coarsetofine_addcontrastive.py b3b7c1c716f4ca66 ran · honoured contract fingerprinted 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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