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parse_index_file

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

parse_index_file appears in the code Syntology harvested for 54 papers, as 4 distinct code bodies found in 55 places (a place is one code body under one paper). At least one of them ran in 53 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 parse_index_file 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 4 distinct code bodies named parse_index_file; 1 is unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

3ran · honoured contract

0ran · violated contract

0ran · our draft was wrong

0ran · fixture could not drive it

0ran

1unverified

0fingerprinted

Licence is a property of each copy, so it is counted per place: 19 of the 55 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

54 papers shown of 54, newest first; 55 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; 3 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.

Paper	Date	File	Status Syntology	Licence
Training Robust Graph Neural Networks by Modeling Noise Dependencies	27 Feb 2025	identical code first harvested elsewhere `c1d6392f89c5e495`	ran · honoured contract	licence of this copy not recorded
Non-Homophilic Graph Pre-Training and Prompt Learning	22 Aug 2024	identical code first harvested elsewhere `c1d6392f89c5e495`	ran · honoured contract	licence of this copy not recorded
Distance Recomputator and Topology Reconstructor for Graph Neural Networks	25 Jun 2024	NoakLiu/Distance-Recomputator-and-Topology-Reconstructor/APPNP_GDRA/data_preprocesing.py `5c3fa9402a9405bc`	ran · honoured contract	no licence file found · pointer only
Graph Adversarial Diffusion Convolution	4 Jun 2024	songtaoliu0823/gadc/Adaptive_Adversarial_Attack/utils.py `c1d6392f89c5e495`	ran · honoured contract	no licence file found · pointer only
Hyperbolic Geometric Latent Diffusion Model for Graph Generation	6 May 2024	ringbdstack/hypdiff/data.py `5c3fa9402a9405bc`	ran · honoured contract	no licence file found · pointer only
Combating Bilateral Edge Noise for Robust Link Prediction	2 Nov 2023	flyingdoog/PTDNet/utils.py `c1d6392f89c5e495`	ran · honoured contract	no licence file found · pointer only
Robust Graph Clustering via Meta Weighting for Noisy Graphs	1 Nov 2023	hyeonsoojo/metagc/utils/load_utils.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Simple and Asymmetric Graph Contrastive Learning without Augmentations	29 Oct 2023	graphdml-uiuc-jlu/geom-gcn/utils.py `c1d6392f89c5e495`	ran · honoured contract	no licence file found · pointer only
PSP: Pre-Training and Structure Prompt Tuning for Graph Neural Networks	26 Oct 2023	gqq1210/psp/PSP_graph/utils.py `c1d6392f89c5e495`	ran · honoured contract	no licence file found · pointer only
CONVERT:Contrastive Graph Clustering with Reliable Augmentation	17 Aug 2023	xihongyang1999/convert/utils.py `5c3fa9402a9405bc`	ran · honoured contract	no licence file found · pointer only
Implicit Graph Neural Diffusion Networks: Convergence, Generalization, and Over-Smoothing	7 Aug 2023	guoji-fu/dignn/nodeclassification/data.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation	15 Jun 2023	tmlr-group/MC-GRA/MC-GRA/dataset.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Specformer: Spectral Graph Neural Networks Meet Transformers	2 Mar 2023	DSL-Lab/Specformer/Node/preprocess_node_data.py `c1d6392f89c5e495`	ran · honoured contract	GPL-3.0 (copyleft) · pointer only
Unsupervised Graph Outlier Detection: Problem Revisit, New Insight, and Superior Method	24 Oct 2022	identical code first harvested elsewhere `c1d6392f89c5e495`	ran · honoured contract	licence of this copy not recorded
MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution	15 Aug 2022	wendongbi/MMGNN/main/process.py `c1d6392f89c5e495`	ran · honoured contract	MIT recorded; this copy not marked cleared · pointer only
A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks	9 Jun 2022	oom-debugger/ijcai23/GCNII-master/process.py `c1d6392f89c5e495`	ran · honoured contract	Apache-2.0 (permissive)
Calibrate and Debias Layer-wise Sampling for Graph Convolutional Networks	1 Jun 2022	identical code first harvested elsewhere `c1d6392f89c5e495`	ran · honoured contract	licence of this copy not recorded
Graph Ordering Attention Networks	11 Apr 2022	michailchatzianastasis/goat/utils2.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks	1 Mar 2022	graph-com/peg/utils.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks	28 Jan 2022	yh-yao/FedGCN/src/data_process.py `d2d6d7748327bbb9`	unverified	MIT (permissive)
Towards Unsupervised Deep Graph Structure Learning	17 Jan 2022	grand-lab/sublime/data_loader.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Adaptive Kernel Graph Neural Network	8 Dec 2021	jumxglhf/akgnn/utils.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Robustness of Graph Neural Networks at Scale	26 Oct 2021	ventr1c/res-gcl/dataset.py `5c3fa9402a9405bc`	ran · honoured contract	Apache-2.0 (permissive)
SCE: Scalable Network Embedding from Sparsest Cut	30 Jun 2020	szzhang17/Sparsest-Cut-Network-Embedding/utils.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs	20 Jun 2020	PetarV-/GAT/utils/process.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Bandit Samplers for Training Graph Neural Networks	10 Jun 2020	xavierzw/ogb-geniepath-bs/utils.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Graph Random Neural Network for Semi-Supervised Learning on Graphs	22 May 2020	Grand20/grand/pygcn/utils.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Unifying Graph Convolutional Neural Networks and Label Propagation	17 Feb 2020	achalagarwal/gcn-lpa/src/data_loader.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Geom-GCN: Geometric Graph Convolutional Networks	13 Feb 2020	bingzhewei/geom-gcn/utils.py `dfd091f34611a47a`	ran · honoured contract	no licence file found · pointer only
AnomalyDAE: Dual autoencoder for anomaly detection on attributed networks	10 Feb 2020	haoyfan/AnomalyDAE/src/input_data.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks	17 Nov 2019	identical code first harvested elsewhere `c1d6392f89c5e495`	ran · honoured contract	licence of this copy not recorded
GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction	5 Nov 2019	CRIPAC-DIG/GraphAIR/tensorflow_code/utils.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Semi-Implicit Graph Variational Auto-Encoders	19 Aug 2019	identical code first harvested elsewhere `5c3fa9402a9405bc`	ran · honoured contract	licence of this copy not recorded
RWR-GAE: Random Walk Regularization for Graph Auto Encoders	12 Aug 2019	MysteryVaibhav/DW-GAE/gae/utils.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Position-aware Graph Neural Networks	11 Jun 2019	JiaxuanYou/P-GNN/dataset.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	5 Jun 2019	PwnerHarry/Stronger_GCN/TF2/initialize_dataset.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Deep Bayesian Optimization on Attributed Graphs	31 May 2019	csjtx1021/DGBO/gcn/utils.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Simplifying Graph Convolutional Networks	19 Feb 2019	Tiiiger/SGC/utils.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification	13 Feb 2019	CRIPAC-DIG/H-GCN/tensorflow_code/utils.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Label Efficient Semi-Supervised Learning via Graph Filtering	28 Jan 2019	liqimai/Efficient-SSL/gcn/utils.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning	24 Jan 2019	malllabiisc/ConfGCN/helper.py `c1d6392f89c5e495`	ran · honoured contract	Apache-2.0 (permissive)
Bayesian graph convolutional neural networks for semi-supervised classification	27 Nov 2018	huawei-noah/BGCN/src/utils_gcn.py `c1d6392f89c5e495`	ran · honoured contract	MIT recorded; this copy not marked cleared · pointer only
Multi-Task Graph Autoencoders	7 Nov 2018	vuptran/graph-representation-learning/longae/utils_gcn.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
A Recurrent Graph Neural Network for Multi-Relational Data	5 Nov 2018	bioannidis/adaptive_recurrent_graph_neural_network/utils.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Deep Graph Infomax	27 Sep 2018	identical code first harvested elsewhere `c1d6392f89c5e495`	ran · honoured contract	licence of this copy not recorded
Graph Convolutional Neural Networks via Scattering	31 Mar 2018	identical code first harvested elsewhere `c1d6392f89c5e495`	ran · honoured contract	licence of this copy not recorded
Graph Convolutional Neural Networks via Scattering	31 Mar 2018	dmzou/SCAT/trainCora.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models	24 Feb 2018	snap-stanford/GraphRNN/data.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Graph Attention Networks	30 Oct 2017	404nofound/gat/utils/process.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Stochastic Training of Graph Convolutional Networks with Variance Reduction	29 Oct 2017	thu-ml/stochastic_gcn/gcn/utils.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
Variational Graph Auto-Encoders	21 Nov 2016	Omairss/RepresentationLearning/src/input_data.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
Revisiting Semi-Supervised Learning with Graph Embeddings	29 Mar 2016	asarigun/la-gcn-tensorflow/utils.py `c1d6392f89c5e495`	ran · honoured contract	MIT (permissive)
arXiv:ijcai2022_0498		xinxingwu-uk/DGAE/Python/Models/dgae_alpha/input_data.py `5c3fa9402a9405bc`	ran · honoured contract	MIT (permissive)
arXiv:aaai_20873		RICE-EIC/Early-Bird-GCN/gcn/utils.py `c1d6392f89c5e495`	ran · honoured contract	Apache-2.0 (permissive)
arXiv:aaai_20664		jumxglhf/AKGNN/utils.py `5c3fa9402a9405bc`	ran · honoured contract	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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