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get_arguments

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

get_arguments appears in the code Syntology harvested for 15 papers, as 17 distinct code bodies found in 18 places (a place is one code body under one paper). At least one of them ran in 6 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_arguments 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 5 of the 17 distinct code bodies named get_arguments; 12 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
4ran · our draft was wrong
0ran · fixture could not drive it
1ran
12unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 4 of the 18 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

15 papers shown of 15, newest first; 18 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. 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
Perturb a Model, Not an Image: Towards Robust Privacy Protection via Anti-Personalized Diffusion Models added by Syntology 2025-11 (from id) KU-VGI/APDM/gen_arguments.py 24839e38b640f364 unverified no licence file found · pointer only
Implicitly Aligning Humans and Autonomous Agents through Shared Task Abstractions 7 May 2025 HIRO-group/HA2/oai_agents/common/arguments.py 5f6d9fe3bb842d1a unverified MIT (permissive)
Improving Antibody Humanness Prediction using Patent Data 25 Jan 2024 AstraZeneca/SelfPAD/utils_common/arguments.py e35d7f4b2df4e9c5 ran Apache-2.0 (permissive)
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library 25 Dec 2023 agi-brain/xuance/xuance/common/common_tools.py 5824a7722625e41d unverified MIT (permissive)
Unifying Short and Long-Term Tracking with Graph Hierarchies 6 Dec 2022 dvl-tum/SUSHI/configs/config.py a03bcbfa3e6634c3 unverified MIT (permissive)
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs 30 May 2022 yangzez/ood-link-prediction-generalization-mpnn/link_prediction_new.py 84489b1dfc1645d1 unverified MIT (permissive)
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs 30 May 2022 yangzez/ood-link-prediction-generalization-mpnn/link_prediction_new_ddi.py 7ba79e79c5b339f8 unverified MIT (permissive)
Transformer for Partial Differential Equations' Operator Learning 26 May 2022 BaratiLab/OFormer/BVP/utils.py 98e289ae1b56d7c0 unverified MIT (permissive)
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids 1 Dec 2021 peterbjorgensen/DeepDFT/evaluate_model.py f6aabd567b2d4c93 unverified MIT (permissive)
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids 1 Dec 2021 peterbjorgensen/DeepDFT/predict_with_model.py 0f30abcc0b06a84d unverified MIT (permissive)
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids 1 Dec 2021 peterbjorgensen/DeepDFT/runner.py 84cd611d44e7b78a unverified MIT (permissive)
Cross-View Regularization for Domain Adaptive Panoptic Segmentation 3 Mar 2021 jxhuang0508/CVRN/cvrn_train_r/ADVENT/CRST/crst_seg_aux_ss_trg_cross_style_pseudo_label_generation.py b20b4bad4dba8d25 unverified MIT (permissive)
Single-Stage Semantic Segmentation from Image Labels 16 May 2020 visinf/1-stage-wseg/opts.py 1f3ecbd451a206b3 unverified Apache-2.0 (permissive)
Molecule Property Prediction and Classification with Graph Hypernetworks 1 Feb 2020 galkampel/HyperNetworks/train_nmp.py 997f55dd13cd2c51 ran · our draft was wrong no licence file found · pointer only
SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action Recognition 30 Jul 2019 carloscaetano/skeleton-images/GenerateSkeletonImages.py c6322ba2c1b13230 ran · our draft was wrong no licence file found · pointer only
Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials 8 Jun 2018 identical code first harvested elsewhere c3c3392a3d0f7172 ran · our draft was wrong licence of this copy not recorded
SchNet - a deep learning architecture for molecules and materials 2017-12 (from id) peterbjorgensen/msgnet/src/scripts/runner.py c3c3392a3d0f7172 ran · our draft was wrong MIT (permissive)
Multi-Dimensional Recurrent Neural Networks 14 May 2007 philipperemy/tensorflow-multi-dimensional-lstm/trainer.py bf26c8d187534a2d ran · our draft was wrong 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".

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