Home › Code › get_test_records

get_test_records

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

get_test_records appears in the code Syntology harvested for 23 papers, as 1 distinct code body found in 23 places (a place is one code body under one paper). At least one of them ran in 23 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 get_test_records 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 1 of the 1 distinct code body named get_test_records; 0 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

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

Licence is a property of each copy, so it is counted per place: 10 of the 23 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

23 papers shown of 23, newest first; 23 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
LFME: A Simple Framework for Learning from Multiple Experts in Domain Generalization 22 Oct 2024 liangchen527/LFME/domain_generalization/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong no licence file found · pointer only
OT-VP: Optimal Transport-guided Visual Prompting for Test-Time Adaptation 12 Jun 2024 zybeich/ot-vp/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong MIT (permissive)
Causally Inspired Regularization Enables Domain General Representations 25 Apr 2024 olawalesalaudeen/tcri/DomainBed/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong MIT (permissive)
A Causal Inspired Early-Branching Structure for Domain Generalization 13 Mar 2024 liangchen527/causeb/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong no licence file found · pointer only
Understanding Domain Generalization: A Noise Robustness Perspective 26 Jan 2024 qiaoruiyt/NoiseRobustDG/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong MIT (permissive)
Unlocking Emergent Modularity in Large Language Models 17 Oct 2023 qiuzh20/emoe/Vision/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong MIT (permissive)
Invariant Learning via Probability of Sufficient and Necessary Causes 22 Sep 2023 ymy4323460/casn/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong no licence file found · pointer only
Domain Generalization via Rationale Invariance 22 Aug 2023 liangchen527/ridg/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong no licence file found · pointer only
Cross Contrasting Feature Perturbation for Domain Generalization 24 Jul 2023 hackmebroo/ccfp/model_selection.py 53fac8d8d949e72b ran · our draft was wrong no licence file found · pointer only
An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration 17 Jul 2023 hiroki11x/timm_ood_calibration/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong Apache-2.0 (permissive)
PGrad: Learning Principal Gradients For Domain Generalization 2 May 2023 qdata/pgrad/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong MIT (permissive)
TFS-ViT: Token-Level Feature Stylization for Domain Generalization 28 Mar 2023 mehrdad-noori/tfs-vit_token-level_feature_stylization/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong MIT (permissive)
Empirical Study on Optimizer Selection for Out-of-Distribution Generalization 15 Nov 2022 hiroki11x/optimizer_comparison_ood/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong Apache-2.0 (permissive)
Prompt Vision Transformer for Domain Generalization 18 Aug 2022 zhengzangw/DoPrompt/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong MIT (permissive)
Test-Time Adaptation via Self-Training with Nearest Neighbor Information 8 Jul 2022 mingukjang/tast/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong MIT recorded; this copy not marked cleared · pointer only
Sparse Mixture-of-Experts are Domain Generalizable Learners 8 Jun 2022 luodian/sf-moe-dg/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong MIT recorded; this copy not marked cleared · pointer only
FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction 26 May 2022 lins-lab/fedbr/fedbr/model_selection.py 53fac8d8d949e72b ran · our draft was wrong Apache-2.0 (permissive)
Diverse Weight Averaging for Out-of-Distribution Generalization 19 May 2022 alexrame/diwa/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong Apache-2.0 (permissive)
Towards Principled Disentanglement for Domain Generalization 27 Nov 2021 identical code first harvested elsewhere 53fac8d8d949e72b ran · our draft was wrong licence of this copy not recorded
Domain Prompt Learning for Efficiently Adapting CLIP to Unseen Domains 25 Nov 2021 shogi880/DPLCLIP/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong MIT recorded; this copy not marked cleared · pointer only
SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of Invariances in Domain Generalization 4 Jun 2021 shahtalebi/SAND-mask/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong MIT recorded; this copy not marked cleared · pointer only
Invariant Risk Minimization 5 Jul 2019 katoro8989/irm_variants_calibration/domainbed/model_selection.py 53fac8d8d949e72b ran · our draft was wrong Apache-2.0 (permissive)
Deeper, Broader and Artier Domain Generalization 9 Oct 2017 hlzhang109/ddg/model_selection.py 53fac8d8d949e72b ran · our draft was wrong 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