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create_loss

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

create_loss appears in the code Syntology harvested for 11 papers, as 12 distinct code bodies found in 14 places (a place is one code body under one paper). At least one of them ran in 7 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 create_loss 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 7 of the 12 distinct code bodies named create_loss; 5 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
2ran · our draft was wrong
0ran · fixture could not drive it
5ran
5unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 4 of the 14 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

11 papers shown of 11, newest first; 14 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
Federated Representation Learning in the Under-Parameterized Regime 7 Jun 2024 RenpuLiu/flute/utils/bsml.py b30a377cff8dd790 ran · our draft was wrong MIT (permissive)
Federated Representation Learning in the Under-Parameterized Regime 7 Jun 2024 RenpuLiu/flute/models/bsml.py 1cc29ca74b9238bb ran MIT (permissive)
Robust Training of Federated Models with Extremely Label Deficiency 22 Feb 2024 tmlr-group/Twin-sight/loss_fn/build.py 4aab447e9b17254e ran MIT (permissive)
Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable? 24 Jan 2024 sonialagunac/Beyond-CBM/losses.py fdebfb1784d89686 ran no licence file found · pointer only
Adaptive Test-Time Personalization for Federated Learning 28 Oct 2023 baowenxuan/atp/src/algorithm/ATPTest.py d82d69d3e18a9cd9 ran · our draft was wrong no licence file found · pointer only
Studying K-FAC Heuristics by Viewing Adam through a Second-Order Lens 23 Oct 2023 rmclarke/adamthroughasecondorderlens/models.py d9123205375186bb unverified no licence file found · pointer only
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning 8 Oct 2023 visitworld123/fedfed/loss_fn/build.py 4aab447e9b17254e ran MIT (permissive)
Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox 17 Jul 2023 SSSKJ/HeroLT/HeroLT/nn/Loss/BalancedSoftmaxLoss.py 2c5959a4a4cf5260 ran MIT (permissive)
Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox 17 Jul 2023 SSSKJ/HeroLT/HeroLT/nn/Loss/DiscCentroidsLoss.py 756b76bed831be5a ran MIT (permissive)
Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox 17 Jul 2023 SSSKJ/HeroLT/HeroLT/nn/Loss/SoftmaxLoss.py 247a09b49a2abf27 unverified MIT (permissive)
Decoupled Training for Long-Tailed Classification With Stochastic Representations 19 Apr 2023 zhmiao/OpenLongTailRecognition-OLTR/loss/DiscCentroidsLoss.py 84954cc67863b073 unverified BSD-3-Clause (permissive)
A Benchmark and a Baseline for Robust Multi-view Depth Estimation 13 Sep 2022 lmb-freiburg/robustmvd/rmvd/loss/factory.py 4fd118b76e65dd5b unverified Apache-2.0 (permissive)
Balanced Meta-Softmax for Long-Tailed Visual Recognition 21 Jul 2020 jiawei-ren/BalancedMetaSoftmax-Classification/loss/BalancedSoftmaxLoss.py b30a377cff8dd790 ran · our draft was wrong licence not identified · pointer only
Evaluation of Appearance-Based Methods and Implications for Gaze-Based Applications 2019-01 (from id) hysts/pytorch_mpiigaze/gaze_estimation/losses.py a948c2306c407fae 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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