Paper Citation Record · LEDGER

Self-Reinforced Graph Contrastive Learning

As of 20 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2505.13650.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.13650 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:15:58.877013Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

verified exact0
verified fuzzy20
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 630b155e-7f73-41f5-af30-14f7423d7b3e · outbound

This paper cites Information network or social network? the structure of the twitter follow graph,.

Self-Reinforced Graph Contrastive Learning Information network or social network? the structure of the twitter follow graph,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.308329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fd529c9e-a56a-4c29-b4fc-34bc81d1b20f · outbound

This paper cites Protein function prediction via graph ker- nels,.

Self-Reinforced Graph Contrastive Learning Protein function prediction via graph ker- nels,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.298075Z

Source-reported events for the cited work

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Observation d2aa5e11-7f8e-4f35-9706-9a9e85e73dcb · outbound

This paper cites Knowledge graphs,.

Self-Reinforced Graph Contrastive Learning Knowledge graphs,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.287582Z

Source-reported events for the cited work

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Observation 3be10ffb-ffd8-4dd8-a697-ff8c749bc25e · outbound

This paper cites Graph neural networks for social recommendation,.

Self-Reinforced Graph Contrastive Learning Graph neural networks for social recommendation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.276911Z

Source-reported events for the cited work

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Observation affa1d86-42e5-4117-bbed-fda062d096e2 · outbound

This paper cites Graph con- trastive learning with augmentations,.

Self-Reinforced Graph Contrastive Learning Graph con- trastive learning with augmentations,

Reference 5

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Source-reported events for the cited work

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Observation 94b86fb8-f783-406a-bbe0-ef91a8423b2e · outbound

This paper cites Contrastive multi-view represen- tation learning on graphs,.

Self-Reinforced Graph Contrastive Learning Contrastive multi-view represen- tation learning on graphs,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:15:58.735508Z

Source-reported events for the cited work

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Observation ed22ad1e-755b-4baf-b554-a1fcd030fecb · outbound

This paper cites InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization.

Self-Reinforced Graph Contrastive Learning InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:15:58.739423Z

Source-reported events for the cited work

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Observation 559896ae-88e9-41f7-9bbd-40f77cfdf001 · outbound

This paper cites Simgrace: A simple framework for graph contrastive learning without data augmentation,.

Self-Reinforced Graph Contrastive Learning Simgrace: A simple framework for graph contrastive learning without data augmentation,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T20:15:58.744042Z

Source-reported events for the cited work

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Observation fbd59bbb-59b8-4b7c-92ff-0abac2f876ee · outbound

This paper cites Graph contrastive learning automated,.

Self-Reinforced Graph Contrastive Learning Graph contrastive learning automated,

Reference 9

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Source-reported events for the cited work

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Observation 001c4a83-86c2-414b-ad89-06ca10389a77 · outbound

This paper cites Adversarial graph augmentation to improve graph contrastive learning,.

Self-Reinforced Graph Contrastive Learning Adversarial graph augmentation to improve graph contrastive learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.234974Z

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Observation 53e67b7f-ebb4-4550-b58b-8c8c8dfdaa1c · outbound

This paper cites Autogcl: Automated graph contrastive learning via learnable view generators,.

Self-Reinforced Graph Contrastive Learning Autogcl: Automated graph contrastive learning via learnable view generators,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.223327Z

Source-reported events for the cited work

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Observation 78786fee-cd6f-4626-a89c-9af6ae6108a7 · outbound

This paper cites Structure-activity relationship of mutagenic aromatic and heteroaromatic nitro compounds. correlation with molecular orbital energies and hydrophobicity,.

Self-Reinforced Graph Contrastive Learning Structure-activity relationship of mutagenic aromatic and heteroaromatic nitro compounds. correlation with molecular orbital energies and hydrophobicity,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.212990Z

Source-reported events for the cited work

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Observation 5a21abe0-9e23-499e-820c-45741dd006e5 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

Self-Reinforced Graph Contrastive Learning Momentum contrast for unsupervised visual representation learning,

Reference 13

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Source-reported events for the cited work

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Observation 409cd98a-7126-43b4-a8e2-8b1b0a26ca23 · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

Self-Reinforced Graph Contrastive Learning A simple framework for contrastive learning of visual representations,

Reference 14

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Source-reported events for the cited work

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Observation 4550a5a7-4556-42c6-82c5-f978bb2864f5 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Self-Reinforced Graph Contrastive Learning Representation Learning with Contrastive Predictive Coding

Reference 15

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Source-reported events for the cited work

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Observation 6f315081-698d-4b16-ad77-912f4028d2d3 · outbound

This paper cites A global geometric framework for nonlinear dimensionality reduction,.

Self-Reinforced Graph Contrastive Learning A global geometric framework for nonlinear dimensionality reduction,

Reference 16

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Observation 2e8948c1-dbc0-4180-ba10-94c32ff701eb · outbound

This paper cites Representation learning: A review and new perspectives,.

Self-Reinforced Graph Contrastive Learning Representation learning: A review and new perspectives,

Reference 17

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Source-reported events for the cited work

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Observation ff01ef2b-d24a-4588-a937-76f2e4ae1e4f · outbound

This paper cites Manifold structure in graph embeddings,.

Self-Reinforced Graph Contrastive Learning Manifold structure in graph embeddings,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.175281Z

Source-reported events for the cited work

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Observation 61a00f3c-7299-47c4-aae1-769543a83b74 · outbound

This paper cites A Manifold Perspective on the Statistical Generalization of Graph Neural Networks.

Self-Reinforced Graph Contrastive Learning A Manifold Perspective on the Statistical Generalization of Graph Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T20:15:58.784808Z

Source-reported events for the cited work

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Observation 22d3c38e-02b0-41c7-98e3-683cea1382ba · outbound

This paper cites An experimental study of the decay of temperature fluctuations in grid-generated turbulence,.

Self-Reinforced Graph Contrastive Learning An experimental study of the decay of temperature fluctuations in grid-generated turbulence,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.163915Z

Source-reported events for the cited work

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Observation 77954573-45c7-42be-a245-b414e540c759 · outbound

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Self-Reinforced Graph Contrastive Learning Unresolved cited work

Reference 21

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Observation 44892ae0-6e7a-4ef3-bf47-b9125607bec1 · outbound

This paper cites On upstream differencing and godunov-type schemes for hyperbolic conservation laws,.

Self-Reinforced Graph Contrastive Learning On upstream differencing and godunov-type schemes for hyperbolic conservation laws,

Reference 22

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Observation 6516ef19-acc2-487e-8785-c2be0365e240 · outbound

This paper cites Statistical guarantees for the em algorithm: From population to sample-based analysis,.

Self-Reinforced Graph Contrastive Learning Statistical guarantees for the em algorithm: From population to sample-based analysis,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.140635Z

Source-reported events for the cited work

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Observation 2839ddc8-190f-4d83-879e-d676ebdb1397 · outbound

This paper cites Weakly- and semi-supervised learning of a deep convolutional network for semantic image segmentation,.

Self-Reinforced Graph Contrastive Learning Weakly- and semi-supervised learning of a deep convolutional network for semantic image segmentation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.128540Z

Source-reported events for the cited work

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Observation 1f455da2-d9c5-4f2d-b4cd-d9497692bd29 · outbound

This paper cites High-dimensional variance- reduced stochastic gradient expectation-maximization algorithm,.

Self-Reinforced Graph Contrastive Learning High-dimensional variance- reduced stochastic gradient expectation-maximization algorithm,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2796dd6c-8fec-493f-8ae9-2727bcddbd3b · outbound

This paper cites TUDataset: A collection of benchmark datasets for learning with graphs.

Self-Reinforced Graph Contrastive Learning TUDataset: A collection of benchmark datasets for learning with graphs

Reference 26

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This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Self-Reinforced Graph Contrastive Learning Pytorch: An imperative style, high-performance deep learning library,

Reference 27

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Observation afa4f420-ca07-4da9-82a2-f59f389d0c27 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Self-Reinforced Graph Contrastive Learning Fast Graph Representation Learning with PyTorch Geometric

Reference 28

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Observation 5cfe4431-bcd2-483e-930b-f9e63c6a1dff · outbound

This paper cites Learning convolutional neural networks for graphs,.

Self-Reinforced Graph Contrastive Learning Learning convolutional neural networks for graphs,

Reference 29

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Source-reported events for the cited work

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Observation 9bf1a8cc-d84e-4498-b545-16aaa9357b80 · outbound

This paper cites Support vector machines for classifi- cation and regression,.

Self-Reinforced Graph Contrastive Learning Support vector machines for classifi- cation and regression,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.087948Z

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Observation ff7b8194-da6f-44b2-9eb9-55044f4e2bb5 · outbound

This paper cites Efficient graphlet kernels for large graph comparison,.

Self-Reinforced Graph Contrastive Learning Efficient graphlet kernels for large graph comparison,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.076644Z

Source-reported events for the cited work

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Observation 55638569-5e3f-4f59-832c-d3e0bfad3ad1 · outbound

This paper cites Weisfeiler-lehman graph kernels.

Self-Reinforced Graph Contrastive Learning Weisfeiler-lehman graph kernels

Reference 32

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Source-reported events for the cited work

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Observation ad647cb0-f44d-435e-ad3b-4284448da87d · outbound

This paper cites Deep graph kernels,.

Self-Reinforced Graph Contrastive Learning Deep graph kernels,

Reference 33

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Observation 2ce90622-e412-431c-a24d-7d0016f83a9a · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Self-Reinforced Graph Contrastive Learning Semi-Supervised Classification with Graph Convolutional Networks

Reference 34

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This paper cites Inductive representation learning on large graphs,.

Self-Reinforced Graph Contrastive Learning Inductive representation learning on large graphs,

Reference 35

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This paper cites How Powerful are Graph Neural Networks?.

Self-Reinforced Graph Contrastive Learning How Powerful are Graph Neural Networks?

Reference 36

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Source-reported events for the cited work

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Observation a5f4d316-bc69-4f92-b2ab-6a3e95cabfec · outbound

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Self-Reinforced Graph Contrastive Learning Graph attention networks,

Reference 37

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Observation c3e84393-6c58-4d68-b71f-50f7d1613178 · outbound

This paper cites node2vec: Scalable feature learning for networks,.

Self-Reinforced Graph Contrastive Learning node2vec: Scalable feature learning for networks,

Reference 38

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Source-reported events for the cited work

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Observation dda46fa1-3e48-4cdd-8226-5b61cf4cefe9 · outbound

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Self-Reinforced Graph Contrastive Learning Sub2vec: Feature learning for subgraphs,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.027305Z

Source-reported events for the cited work

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Observation 2b691a89-e02f-490c-9b14-29b2d0bf857e · outbound

This paper cites graph2vec: Learning Distributed Representations of Graphs.

Self-Reinforced Graph Contrastive Learning graph2vec: Learning Distributed Representations of Graphs

Reference 40

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Observation c08c5ba7-8cd9-4f0c-afd8-714495ce4714 · outbound

This paper cites A Fair Comparison of Graph Neural Networks for Graph Classification.

Self-Reinforced Graph Contrastive Learning A Fair Comparison of Graph Neural Networks for Graph Classification

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T20:15:58.866011Z

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Observation 52d5361d-4f26-4d72-a951-6950c3fae754 · outbound

This paper cites Autogcl github repository.

Self-Reinforced Graph Contrastive Learning Autogcl github repository

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.015844Z

Source-reported events for the cited work

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Observation ba03ac74-e8c5-4dc6-a62e-fd2eda5e4b0c · outbound

This paper cites I-divergence geometry of probability distributions and min- imization problems,.

Self-Reinforced Graph Contrastive Learning I-divergence geometry of probability distributions and min- imization problems,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:15:59.003982Z

Source-reported events for the cited work

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Observation df19d90d-6c00-47bc-ac6e-a43bb39869c5 · outbound

This paper cites Markov processes over denumerable products of spaces, describing large systems of automata,.

Self-Reinforced Graph Contrastive Learning Markov processes over denumerable products of spaces, describing large systems of automata,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T20:15:58.877013Z

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