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get_parameters

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

get_parameters appears in the code Syntology harvested for 30 papers, as 21 distinct code bodies found in 31 places (a place is one code body under one paper). At least one of them ran in 10 of the papers; 1 of the code bodies carries 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_parameters 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 21 distinct code bodies named get_parameters; 12 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

1ran · honoured contract
0ran · violated contract
5ran · our draft was wrong
0ran · fixture could not drive it
3ran
12unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 8 of the 31 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

30 papers shown of 30, newest first; 31 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 4 papers added by Syntology. 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
Contraction and Hourglass Persistence for Learning on Graphs, Simplices, and Cells added by Syntology 2026-04 (from id) Aalto-QuML/Hourglass/experiment.py 17eb2746c0fdb30c unverified MIT (permissive)
SafeAdapt: Provably Safe Policy Updates in Deep Reinforcement Learning added by Syntology 2026-04 (from id) maxanisimov/provably-safe-policy-updates/abstract_gradient_training/model_utils.py d7a1d7a0a22bcfcb unverified MIT (permissive)
Bikelution: Federated Gradient-Boosting for Scalable Shared Micro-Mobility Demand Forecasting added by Syntology 2026-02 (from id) DataStories-UniPi/Bikelution/src/helper.py f2d3a731c98a9cf0 unverified GPL-3.0 (copyleft) · pointer only
Fly-CL: A Fly-Inspired Framework for Enhancing Efficient Decorrelation and Reduced Training Time in Pre-trained Model-based Continual Representation Learning added by Syntology 2025-10 (from id) gfyddha/Fly-CL/utils.py 7c91acbf1ec3dfec unverified MIT (permissive)
A Large-Scale Study on Video Action Dataset Condensation 30 Dec 2024 mcg-nju/video-dc/utils.py 9a700a3b149f4952 unverified Apache-2.0 (permissive)
DELT: A Simple Diversity-driven EarlyLate Training for Dataset Distillation 29 Nov 2024 vila-lab/delt/evaluation/validation/utils.py 9a700a3b149f4952 unverified no licence file found · pointer only
RMB: Comprehensively Benchmarking Reward Models in LLM Alignment 13 Oct 2024 zhou-zoey/rmb-reward-model-benchmark/eval/scripts/my_run_rm.py ad14d89d1d8e6f44 ran · honoured contract no licence file found · pointer only
Fine-Tuning is Fine, if Calibrated 24 Sep 2024 OSU-MLB/Fine-Tuning-Is-Fine-If-Calibrated/py/util/model.py d829c6631f3d92c6 ran MIT (permissive)
D$^4$M: Dataset Distillation via Disentangled Diffusion Model 21 Jul 2024 richards94/D4M/validate/utils.py 9a700a3b149f4952 unverified BSD-2-Clause (permissive)
Certification for Differentially Private Prediction in Gradient-Based Training 19 Jun 2024 psosnin/AbstractGradientTraining/abstract_gradient_training/model_utils.py d7a1d7a0a22bcfcb unverified GPL-3.0 (copyleft) · pointer only
Mitigating Boundary Ambiguity and Inherent Bias for Text Classification in the Era of Large Language Models 11 Jun 2024 chuge0335/pc-cot/construct_prompt.py f7289b4621cb8dfe ran fingerprinted no licence file found · pointer only
Mapping the Multiverse of Latent Representations 2 Feb 2024 aidos-lab/Presto/lsd/utils.py 281e62c87492afd4 ran BSD-3-Clause (permissive)
On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm 6 Dec 2023 lins-lab/rded/validation/utils.py 9a700a3b149f4952 unverified Apache-2.0 (permissive)
Going beyond persistent homology using persistent homology 10 Nov 2023 Aalto-QuML/RePHINE/experiment.py 17eb2746c0fdb30c unverified no licence file found · pointer only
Adaptive Compression in Federated Learning via Side Information 22 Jun 2023 francescopase/federated-klms/flower_fl/utils/models.py f2d3a731c98a9cf0 unverified MIT (permissive)
GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting 28 Feb 2023 lkyddd/GradMA/LightFed/experiments/horizontal/GradMA/trainer.py 0d624202e744b125 ran · our draft was wrong no licence file found · pointer only
Federated Survival Forests 6 Feb 2023 archettialberto/federated_survival_forests/utils.py 9b13c88ff5cc9398 unverified MIT (permissive)
Textual Manifold-based Defense Against Natural Language Adversarial Examples 5 Nov 2022 dangne/tmd/src/train/train_sweep_generator.py e7f49f3930b08c55 unverified MIT (permissive)
Transfer Learning with Deep Tabular Models 30 Jun 2022 levinroman/tabular-transfer-learning/optune_from_scratch.py 6c413ad79849a013 ran · our draft was wrong MIT (permissive)
Influencing Long-Term Behavior in Multiagent Reinforcement Learning 7 Mar 2022 dkkim93/further/algorithm/further/agent.py a460d87b686cc889 ran · our draft was wrong MIT (permissive)
Delaunay Component Analysis for Evaluation of Data Representations 14 Feb 2022 petrapoklukar/dca/dca/loggers.py 84664625dedeb394 unverified MIT (permissive)
Contrastive Active Inference 19 Oct 2021 mazpie/contrastive-aif/agents.py 3091e1fe6e877363 ran · our draft was wrong MIT (permissive)
Dream to Control: Learning Behaviors by Latent Imagination 3 Dec 2019 KohMat/carracing-dreamer/dreamer/utils/freeze_parameter.py c53ea31731e9c271 unverified MIT (permissive)
Dream to Control: Learning Behaviors by Latent Imagination 3 Dec 2019 juliusfrost/dreamer-pytorch/dreamer/utils/module.py 00749ea05ebef1a6 unverified MIT (permissive)
Trivializations for Gradient-Based Optimization on Manifolds 20 Sep 2019 identical code first harvested elsewhere 93fa2cac3cbd6302 ran · our draft was wrong licence of this copy not recorded
Single Path One-Shot Neural Architecture Search with Uniform Sampling 31 Mar 2019 megvii-model/SinglePathOneShot/src/Supernet/utils.py 9a700a3b149f4952 unverified MIT (permissive)
DetNAS: Backbone Search for Object Detection 26 Mar 2019 megvii-model/DetNAS/Supernet-ImageNet/utils.py 9a700a3b149f4952 unverified MIT (permissive)
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group 24 Jan 2019 Lezcano/expRNN/parametrization.py 93fa2cac3cbd6302 ran · our draft was wrong MIT (permissive)
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design 30 Jul 2018 megvii-model/ShuffleNet-Series/ShuffleNetV1/utils.py 9a700a3b149f4952 unverified MIT (permissive)
Data Programming: Creating Large Training Sets, Quickly 25 May 2016 HazyResearch/snorkel/snorkel/map/core.py 9daba8a219f31d0d unverified Apache-2.0 (permissive)
Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding 9 Nov 2015 hosshonarvar/Image-Segmentation/my_code/Src/parameters.py 6b793951869a5684 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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