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load_test_data

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

load_test_data appears in the code Syntology harvested for 21 papers, as 20 distinct code bodies found in 26 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 load_test_data 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 9 of the 20 distinct code bodies named load_test_data; 11 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
1ran · fixture could not drive it
6ran
11unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 7 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

21 papers shown of 21, 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; 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
Faithfulness as Information Flow: Evaluating and Training Faithful Chain-of-Thought Reasoning added by Syntology 2026-05 (from id) safety-research/faithful-cot/eval/compute_faithfulness_from_generations.py 3dce64568cc99197 ran no licence file found · pointer only
Faithfulness as Information Flow: Evaluating and Training Faithful Chain-of-Thought Reasoning added by Syntology 2026-05 (from id) safety-research/faithful-cot/eval/evaluate_hacking_ratio.py c0afdae4075d5d9b ran no licence file found · pointer only
arXiv:2507.11316 2025-07 (from id) hr-jin/ConVA/src/cav_gen.py cfedddf754d3385e ran · fixture could not drive it no licence file found · pointer only
Beyond Cox Models: Assessing the Performance of Machine-Learning Methods in Non-Proportional Hazards and Non-Linear Survival Analysis 24 Apr 2025 compbiomed-unito/survhive/survhive/util.py 179a976dea96da76 unverified MIT (permissive)
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models 10 Jun 2024 richard-peng-xia/CARES/src/eval/eval_multichoice.py ed60b77b1a3f750d ran · our draft was wrong CC-BY-4.0 · pointer only
Language Models Don't Learn the Physical Manifestation of Language 17 Feb 2024 brucewlee/h-test/generate_h_test_training.py 810602b6e416585c ran MIT (permissive)
PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction 13 Feb 2024 lirongwu/psc-cpi/code/dataset.py 62050b71a90939d5 ran MIT (permissive)
Large Language Models Can Learn Temporal Reasoning 12 Jan 2024 xiongsiheng/tg-llm/src/Inference_in_context_learning.py cce7996e68e164e1 unverified MIT (permissive)
OceanNet: A principled neural operator-based digital twin for regional oceans 1 Oct 2023 magray-ncsu/oceannet/data_loader_SSH.py 4627e4b84652343d ran no licence file found · pointer only
OceanNet: A principled neural operator-based digital twin for regional oceans 1 Oct 2023 magray-ncsu/oceannet/data_loader_SSH_two_step.py df2a0db95ac24611 ran no licence file found · pointer only
Is this model reliable for everyone? Testing for strong calibration 28 Jul 2023 jjfeng/testing_strong_calibration/src/subgroup_testing.py 7e1ca43fa2d13b29 ran · our draft was wrong no licence file found · pointer only
Unpaired Image-to-Image Translation via Neural Schrödinger Bridge 24 May 2023 alpc91/NICE-GAN-pytorch/utils.py 8d4ee7233484c7ee unverified MIT (permissive)
Rethinking Explainability as a Dialogue: A Practitioner's Perspective 3 Feb 2022 dylan-slack/talktomodel/experiments/utils.py 4ef7b9ed808f62a2 unverified MIT (permissive)
Sound and Complete Neural Network Repair with Minimality and Locality Guarantees 14 Oct 2021 bu-depend-lab/reassure/ICLR/Experiments/ImageNet/ImageNetTools.py 0414b3043c518f80 unverified MIT (permissive)
Training Generative Adversarial Networks with Limited Data 11 Jun 2020 sangyun884/Face2Webtoon/utils.py 8d4ee7233484c7ee unverified MIT (permissive)
Feature Quantization Improves GAN Training 5 Apr 2020 taki0112/UGATIT/utils.py dcce1222c3697159 unverified MIT (permissive)
U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation 25 Jul 2019 znxlwm/UGATIT-pytorch/utils.py 8d4ee7233484c7ee unverified MIT (permissive)
U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation 25 Jul 2019 WuZhewei/my_First_GAN_tryout/utils.py dcce1222c3697159 unverified MIT (permissive)
U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation 25 Jul 2019 minivision-ai/photo2cartoon/utils/utils.py f2723b22ce3e5bcf unverified MIT (permissive)
DRIT++: Diverse Image-to-Image Translation via Disentangled Representations 2 May 2019 taki0112/DRIT-Tensorflow/utils.py 8d4ee7233484c7ee unverified MIT (permissive)
Image-to-Image Translation via Group-wise Deep Whitening-and-Coloring Transformation 24 Dec 2018 taki0112/GDWCT-Tensorflow/utils.py bb95d212dc8441e6 unverified MIT (permissive)
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design 30 Jul 2018 CellProfiling/HPA-Special-Prize/inference/special_eval.py e5b4c800ffeec6c5 unverified Apache-2.0 (permissive)
Multimodal Unsupervised Image-to-Image Translation 12 Apr 2018 taki0112/MUNIT-Tensorflow/utils.py bb95d212dc8441e6 unverified MIT (permissive)
Unsupervised Image-to-Image Translation Networks 2 Mar 2017 taki0112/UNIT-Tensorflow/DatasetAPI/utils.py 8d4ee7233484c7ee unverified MIT (permissive)
Unsupervised Image-to-Image Translation Networks 2 Mar 2017 taki0112/UNIT-Tensorflow/utils.py c35237a13dc4f943 unverified MIT (permissive)
Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs 30 Mar 2016 kakao/n2/benchmarks/benchmark_script.py 4e54de2be24f817c unverified Apache-2.0 (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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