Paper Citation Record · LEDGER

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning

As of 20 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2412.17468.

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

pith.paper-citation-record.v1
2412.17468 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:32:59.184836Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

17 of 17 outbound references displayed

verified exact2
verified fuzzy1
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 85c0fca2-4eb9-431c-b583-f26327ebb088 · outbound

This paper cites Can Graph Neural Networks Count Substructures?.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Can Graph Neural Networks Count Substructures?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.064897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8cc3862-b3e6-4cfc-bb64-13ae6cf28f11 · outbound

This paper cites The Weisfeiler-Lehman Method and Graph Isomorphism Testing.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning The Weisfeiler-Lehman Method and Graph Isomorphism Testing

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.072685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1183973d-3d57-4d34-84b1-336685d0acba · outbound

This paper cites Topological Graph Neural Networks.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Topological Graph Neural Networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.102048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37f175f1-a268-41d6-bf0e-92a4d0ecd9f3 · outbound

This paper cites Provably Powerful Graph Networks.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Provably Powerful Graph Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.147235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99f239df-0fbb-44ed-8bbd-f6a157bfbf82 · outbound

This paper cites How Powerful are Graph Neural Networks?.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning How Powerful are Graph Neural Networks?

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.160189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f454c28a-cf90-4089-8ba9-201e8e0f67c6 · outbound

This paper cites Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks

Reference 1979

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.022821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03895822-850b-45f3-a364-7abdfa4218d5 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Adam: A Method for Stochastic Optimization

Reference 1992

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.112693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17e84db4-2d5e-4cf6-9eb9-ce354d86263e · outbound

This paper cites Deep Learning with Topological Signatures.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Deep Learning with Topological Signatures

Reference 2002

Resolution: verified exact; local_arxiv, observed 2026-08-11T05:32:59.635408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3fbca16d-37b1-4f55-9e6a-c13d9e7bef98 · outbound

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

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Semi-Supervised Classification with Graph Convolutional Networks

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.125075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16e1593b-466c-4804-adfc-9e5f199561f2 · outbound

This paper cites Hierarchical Graph Representation Learning with Differentiable Pooling.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Hierarchical Graph Representation Learning with Differentiable Pooling

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.179618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1365cc4d-c711-43ca-97d5-8108912abca2 · outbound

This paper cites Covariant Compositional Networks For Learning Graphs.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Covariant Compositional Networks For Learning Graphs

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.136021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03d2baf6-8570-4cea-8acf-5de39eaa891c · outbound

This paper cites Weisfeiler and A.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Weisfeiler and A

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:32:59.834756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 24b6f35f-618c-4997-badc-372e49653afd · outbound

This paper cites Learning metrics for persistence-based summaries and applications for graph classification.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Learning metrics for persistence-based summaries and applications for graph classification

Reference 2018

Resolution: verified exact; local_arxiv, observed 2026-08-11T05:32:59.262426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8ecdf388-8f20-4c01-8133-159fd46030d8 · outbound

This paper cites an unresolved cited work.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Unresolved cited work

Reference 2019

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:32:59.868375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 24cf284f-f40a-48db-a74e-07db5ff4228b · outbound

This paper cites Breaking the Limits of Message Passing Graph Neural Networks.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Breaking the Limits of Message Passing Graph Neural Networks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.035034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4409524-ea89-46e2-a7b2-c3c95c508d8c · outbound

This paper cites Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.041682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1499f29f-c5ae-4c44-9351-244edd17b713 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning Fast Graph Representation Learning with PyTorch Geometric

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T05:32:59.081177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.