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set_optimizer

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

set_optimizer appears in the code Syntology harvested for 24 papers, as 14 distinct code bodies found in 26 places (a place is one code body under one paper). At least one of them ran in 16 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 set_optimizer 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 14 distinct code bodies named set_optimizer; 8 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
4ran · our draft was wrong
0ran · fixture could not drive it
2ran
8unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 10 of the 26 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

24 papers shown of 24, newest first; 26 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
H-SPLID: HSIC-based Saliency Preserving Latent Information Decomposition added by Syntology 2025-10 (from id) neu-spiral/H-SPLID/src/models/split_model.py 7d331d112a46a892 ran · our draft was wrong Apache-2.0 (permissive)
HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection 26 Sep 2024 deeplearning-wisc/haloscope/linear_probe.py a44a1925c2c778ba ran no licence file found · pointer only
Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation 26 Jun 2024 dongguanting/dpa-rag/SupContrast/util.py a44a1925c2c778ba ran no licence file found · pointer only
When and How Does In-Distribution Label Help Out-of-Distribution Detection? 28 May 2024 deeplearning-wisc/id_label/linear_probe.py a44a1925c2c778ba ran no licence file found · pointer only
Contrastive Continual Learning with Importance Sampling and Prototype-Instance Relation Distillation 7 Mar 2024 lijy373/CCLIS/CCLIS/util.py 70bd7d2359734251 ran no licence file found · pointer only
Combating Bilateral Edge Noise for Robust Link Prediction 2 Nov 2023 HobbitLong/SupContrast/util.py a44a1925c2c778ba ran BSD-2-Clause (permissive)
Stop Pre-Training: Adapt Visual-Language Models to Unseen Languages 29 Jun 2023 Yasminekaroui/CliCoTea/src/clicotea/solver.py 98bd09092d99c729 unverified MIT (permissive)
Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification 23 May 2023 raymin0223/patch-mix_contrastive_learning/util/misc.py f100d1606a7ecc2f unverified MIT (permissive)
Pruning Adversarially Robust Neural Networks without Adversarial Examples 9 Oct 2022 neu-spiral/pwoa/source/hsicbt/core/train_misc.py 60f9636984fa3cae unverified MIT (permissive)
Modeling Multiple Views via Implicitly Preserving Global Consistency and Local Complementarity 16 Sep 2022 jiangmengli/coconet/train_CoCoNet.py 083c051b119764dc ran · our draft was wrong no licence file found · pointer only
MetAug: Contrastive Learning via Meta Feature Augmentation 10 Mar 2022 jiangmengli/metaug/train_MetAug.py 5f4842900b5d1d02 ran · our draft was wrong no licence file found · pointer only
MetAug: Contrastive Learning via Meta Feature Augmentation 10 Mar 2022 jiangmengli/metaug/LinearProbing_MetAug.py 3267a33f67aebf53 ran · our draft was wrong no licence file found · pointer only
Generative Models as a Data Source for Multiview Representation Learning 9 Jun 2021 ali-design/GenRep/util.py a44a1925c2c778ba ran MIT (permissive)
Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness 4 Jun 2021 neu-spiral/hbar/source/hbar/core/train_misc.py d7cb7faa3d88e623 unverified MIT (permissive)
Curious Representation Learning for Embodied Intelligence 3 May 2021 yilundu/crl/places_finetune/finetune_places.py c9f9f89dff3b0006 unverified MIT recorded; this copy not marked cleared · pointer only
Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework 6 Aug 2020 identical code first harvested elsewhere 083c051b119764dc ran · our draft was wrong licence of this copy not recorded
Supervised Contrastive Learning 23 Apr 2020 XG293/SupConLoss/util.py a44a1925c2c778ba ran BSD-2-Clause (permissive)
Momentum Contrast for Unsupervised Visual Representation Learning 13 Nov 2019 HobbitLong/CMC/LinearProbing.py 3267a33f67aebf53 ran · our draft was wrong BSD-2-Clause (permissive)
Contrastive Multiview Coding 13 Jun 2019 identical code first harvested elsewhere 3267a33f67aebf53 ran · our draft was wrong licence of this copy not recorded
Contrastive Multiview Coding 13 Jun 2019 danielchyeh/imagenet-100-pytorch/util.py a44a1925c2c778ba ran MIT (permissive)
A Machine Learning Benchmark for Facies Classification 12 Jan 2019 olivesgatech/image-2022-volumetric-contrastive/util.py a44a1925c2c778ba ran BSD-2-Clause (permissive)
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs 27 Feb 2018 xuyxu/Ensemble-Pytorch/torchensemble/utils/set_module.py c5a3a3cd326f2289 unverified BSD-3-Clause (permissive)
Learning Latent Permutations with Gumbel-Sinkhorn Networks 23 Feb 2018 google/gumbel_sinkhorn/optimizer.py a66e302bfd882730 unverified Apache-2.0 (permissive)
arXiv:Zhou_Towards_Effective_Foundation_Model_Adaptation_for_Extreme_Cross-Domain_Few-Shot_Learning_ICCV_2025_paper NWPUZhoufei/FMA/utils.py a44a1925c2c778ba ran Apache-2.0 (permissive)
arXiv:Zhou_Revisiting_Prototypical_Network_for_Cross_Domain_Few-Shot_Learning_CVPR_2023_paper NWPUZhoufei/LDP-Net/utils.py a44a1925c2c778ba ran Apache-2.0 (permissive)
arXiv:Sun_Soteria_Provable_Defense_Against_Privacy_Leakage_in_Federated_Learning_From_CVPR_2021_paper jeremy313/Soteria/GS_attack/inversefed/training/training_routine.py 953df33ba2dfd49e 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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