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SupConLoss

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

SupConLoss appears in the code Syntology harvested for 21 papers, as 25 distinct code bodies found in 25 places (a place is one code body under one paper). At least one of them ran in 21 of the papers; 7 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 SupConLoss 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 24 of the 25 distinct code bodies named SupConLoss; 1 is unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
24ran
1unverified
7fingerprinted

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

21 papers shown of 21, 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, and the graph's for 1 papers added by Syntology; 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
From Vicious to Virtuous Cycles: Synergistic Representation Learning for Unsupervised Video Object-Centric Learning added by Syntology 2026-02 (from id) hynnsk/SRL/srl/losses.py 81aee15db4dfebcb ran · metamorphic tier: invariant MIT (permissive)
Unsupervised Multimodal Clustering for Semantics Discovery in Multimodal Utterances 21 May 2024 thuiar/UMC/methods/unsupervised/UMC/manager.py e0fe559747014274 ran no licence file found · pointer only
UniGen: Universal Domain Generalization for Sentiment Classification via Zero-shot Dataset Generation 2 May 2024 c-juhwan/unigen/task/classification/train_sungen.py e94017f69584a14a ran no licence file found · pointer only
OrCo: Towards Better Generalization via Orthogonality and Contrast for Few-Shot Class-Incremental Learning 27 Mar 2024 noorahmedds/orco/models/orco/Network.py ab68005a9f848926 ran fingerprinted no licence file found · pointer only
Active Generalized Category Discovery 7 Mar 2024 mashijie1028/activegcd/utils_al/train_recipes_ema.py 300b0f6e28f50218 ran MIT (permissive)
Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery 30 Oct 2023 sarahrastegar/infosieve/methods/contrastive_training/contrastive_training.py 9f9e36b6ddd2244e ran fingerprinted MIT (permissive)
Towards Distribution-Agnostic Generalized Category Discovery 2 Oct 2023 jianhongbai/bacon/model/bacon.py 12b38c6451969326 ran MIT (permissive)
Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation 22 Sep 2023 yue-zhongqi/icon/icon/eqinv.py 9e503ad659734ce5 ran MIT (permissive)
Seeing What You Said: Talking Face Generation Guided by a Lip Reading Expert 29 Mar 2023 sxjdwang/talklip/models/learn_sync.py 6e70ca31524ad6fc ran no licence file found · pointer only
SelecMix: Debiased Learning by Contradicting-pair Sampling 4 Nov 2022 iwhwang/SelecMix/module/loss.py 25ed84e39a91b560 ran fingerprinted MIT (permissive)
Large-Scale Pre-training for Person Re-identification with Noisy Labels 30 Mar 2022 DengpanFu/LUPerson/lup_moco/libs/losses.py e853d56ab2fb4cee ran fingerprinted no licence file found · pointer only
Interpretable part-whole hierarchies and conceptual-semantic relationships in neural networks 7 Mar 2022 mmlab-cv/Agglomerator/src/models.py 299961c9af1dd5a2 ran fingerprinted MIT (permissive)
Learning Weakly-Supervised Contrastive Representations 14 Feb 2022 crazy-jack/cl-infonce/clinfonce/losses.py 69b3e18c36d2a734 ran MIT (permissive)
Optimal Representations for Covariate Shift 31 Dec 2021 ryoungj/optdom/DomainBed/domainbed/bottlenecks.py 222beedb5ae19428 ran MIT (permissive)
Few-Shot Intent Detection via Contrastive Pre-Training and Fine-Tuning 13 Sep 2021 ZIZUN/CPFT/finetune/util/model/Classifier_Contrastive.py 68a436d2a91f07aa ran fingerprinted no licence file found · pointer only
Co$^2$L: Contrastive Continual Learning 28 Jun 2021 chaht01/Co2L/losses_negative_only.py c43142360bf64ef4 ran no licence file found · pointer only
FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding 10 Mar 2021 MegviiDetection/FSCE/fsdet/modeling/contrastive_loss.py a99e005b92d2d1b4 ran fingerprinted Apache-2.0 (permissive)
Entity Linking in 100 Languages 5 Nov 2020 hazyresearch/tabi/tabi/models/biencoder.py 808229e9aa41a103 ran Apache-2.0 (permissive)
A Simple Framework for Contrastive Learning of Visual Representations 13 Feb 2020 delyan-boychev/grad-cache-con-learning/src/grad_cache_con_learning/losses.py 19bb24ecb5d473db ran Apache-2.0 (permissive)
A Simple Framework for Contrastive Learning of Visual Representations 13 Feb 2020 hannaiiyanggit/unicon/losses.py a5dbd9a427e2bec3 ran Apache-2.0 (permissive)
A Simple Framework for Contrastive Learning of Visual Representations 13 Feb 2020 Liut2016/ecg-supcontrast/losses.py d8d1dd0aafb92f18 ran · metamorphic tier: invariant BSD-2-Clause (permissive)
A Simple Framework for Contrastive Learning of Visual Representations 13 Feb 2020 rajatkoner08/oodformer/losses.py 1d1a1df3f3426c17 ran no licence file found · pointer only
A Simple Framework for Contrastive Learning of Visual Representations 13 Feb 2020 jwcalder/GraphLearningLayer/losses.py 0e2efd6b67f01d69 unverified MIT (permissive)
XLNet: Generalized Autoregressive Pretraining for Language Understanding 19 Jun 2019 chesterdu/contrastive_summary/src/model.py 624bba127433de69 ran no licence file found · pointer only
arXiv:2024.findings-acl.859 1emonx/Amanda/models/amanda_model.py 90f10d50525407a6 ran 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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