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rand_train_test_idx

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

rand_train_test_idx appears in the code Syntology harvested for 18 papers, as 8 distinct code bodies found in 20 places (a place is one code body under one paper). At least one of them ran in 3 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 rand_train_test_idx 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 3 of the 8 distinct code bodies named rand_train_test_idx; 5 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
1ran · fixture could not drive it
2ran
5unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 8 of the 20 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

18 papers shown of 18, newest first; 20 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 3 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
Heterophily-Agnostic Hypergraph Neural Networks with Riemannian Local Exchanger added by Syntology 2026-03 (from id) Mingzhang21/HealHGNN/HealHGNN/utils/utils.py 5e264c272c383c0c unverified MIT (permissive)
Fixed Aggregation Features Can Rival GNNs added by Syntology 2026-01 (from id) celrm/fixed-aggregation-features/data_utils.py f54bada0dd9396ba unverified no licence file found · pointer only
Glance for Context: Learning When to Leverage LLMs for Node-Aware GNN-LLM Fusion added by Syntology 2025-10 (from id) CUAI/Non-Homophily-Large-Scale/data_utils.py 13234652741e2264 unverified no licence file found · pointer only
One Node One Model: Featuring the Missing-Half for Graph Clustering 13 Dec 2024 xiexuanting/fpgc/FPGC-main/data_utils.py 13234652741e2264 unverified no licence file found · pointer only
Hypformer: Exploring Efficient Hyperbolic Transformer Fully in Hyperbolic Space 1 Jul 2024 Graph-and-Geometric-Learning/hyperbolic-transformer/large/data_utils.py 13234652741e2264 unverified MIT (permissive)
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification 13 Jun 2024 LUOyk1999/tunedGNN/medium_graph/data_utils.py f54bada0dd9396ba unverified MIT (permissive)
SpikeGraphormer: A High-Performance Graph Transformer with Spiking Graph Attention 21 Mar 2024 phd-lanyu/spikegraphormer/medium/data_utils.py cf34dc0377c08698 ran Apache-2.0 (permissive)
SpikeGraphormer: A High-Performance Graph Transformer with Spiking Graph Attention 21 Mar 2024 phd-lanyu/spikegraphormer/large/data_utils.py 13234652741e2264 unverified Apache-2.0 (permissive)
Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace Approach 12 Mar 2024 kkhuang81/AdaptKry/non-homo/data_utils.py 4e2abb5fb81ad073 ran MIT (permissive)
Subgraph Pooling: Tackling Negative Transfer on Graphs 14 Feb 2024 zehong-wang/subgraph-pooling/data_utils.py 13234652741e2264 unverified no licence file found · pointer only
PC-Conv: Unifying Homophily and Heterophily with Two-fold Filtering 22 Dec 2023 uestclbh/pc-conv/data_utils.py 13234652741e2264 unverified no licence file found · pointer only
Graph Transformers for Large Graphs 18 Dec 2023 snap-research/largegt/data.py f54bada0dd9396ba unverified no licence file found · pointer only
arXiv:2310.00800 2023-10 (from id) qitianwu/GraphOOD-EERM/multigraph/data_utils.py 13234652741e2264 unverified no licence file found · pointer only
GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks 20 Jun 2023 wtaozhao/graphglow/data/prep_fb100.py 31a5d29dd4ec41de ran · fixture could not drive it fingerprinted no licence file found · pointer only
SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations 19 Jun 2023 qitianwu/SGFormer/large/data_utils.py 13234652741e2264 unverified MIT (permissive)
SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations 19 Jun 2023 qitianwu/SGFormer/100M/data_utils.py eea43aafe5795815 unverified MIT (permissive)
A Simple and Scalable Graph Neural Network for Large Directed Graphs 14 Jun 2023 seijimaekawa/a2dug/src/data_utils.py 13234652741e2264 unverified MIT (permissive)
Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing 3 Feb 2023 lumia-group/orderedgnn/datasets/datasets_linkx/data_utils.py 13234652741e2264 unverified MIT (permissive)
Revisiting Heterophily For Graph Neural Networks 14 Oct 2022 SitaoLuan/ACM-GNN/ACM-Geometric/data_utils.py e8000a86d21ce0e0 unverified MIT (permissive)
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods 27 Oct 2021 CUAI/Non-Homophily-Benchmarks/data_utils.py 13234652741e2264 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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