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Paper Citation Record · LEDGER

Edge Attention-based Multi-Relational Graph Convolutional Networks

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1802.04944.

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

pith.paper-citation-record.v1
1802.04944 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:59:42.561713Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:26:24.882715Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 24e2e680-e516-4b94-a775-fcd284a3096b · inbound

Sparse hierarchical representation learning on molecular graphs cites this paper.

Sparse hierarchical representation learning on molecular graphs Edge Attention-based Multi-Relational Graph Convolutional Networks

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-14T14:59:42.561713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:59:42.561713Z digest=sha256:5bb462d32a1e8b135d2df6737662ab114317e5b545fe6eb7191fc702b8fe737e

Observation f59d26c1-b82b-4321-a05b-e73acb9e9245 · inbound

Spam Review Detection with Graph Convolutional Networks cites this paper.

Spam Review Detection with Graph Convolutional Networks Edge Attention-based Multi-Relational Graph Convolutional Networks

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-14T11:46:16.591265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:46:16.591265Z digest=sha256:c124b71198c36dd4c86ad9116e6d9ebdf0b2abc6a91fbd5c55b5d76d43379976

Observation ead447cd-a435-4fb8-ac3b-dcd5d3556624 · inbound

Investigating Graph Neural Networks and Classical Feature-Extraction Techniques in Activity-Cliff and Molecular Property Prediction cites this paper.

Investigating Graph Neural Networks and Classical Feature-Extraction Techniques in Activity-Cliff and Molecular Property Prediction Edge Attention-based Multi-Relational Graph Convolutional Networks

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-12T16:20:12.838426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:20:12.838426Z digest=sha256:9f435dd3d50e8aa4f16c52aa6ebba7cb1d78d42d0135ac141e7bf35b44f49e22

Observation 19980cc8-815f-4df6-9189-b5f4b3e0d8bf · inbound

Graph Neural Network Approach to Predicting Magnetization in Quasi-One-Dimensional Ising Systems cites this paper.

Graph Neural Network Approach to Predicting Magnetization in Quasi-One-Dimensional Ising Systems Edge Attention-based Multi-Relational Graph Convolutional Networks

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T14:52:18.887575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:52:18.887575Z digest=sha256:c38c7ec69f80a0e178c25941e159ffb63f02d11b157adc8ad7cc406730ba66cb

Observation 9bd7e25b-5636-4a44-9bf4-8e959c3f19c4 · inbound

Attention-based graph neural networks: a survey cites this paper.

Attention-based graph neural networks: a survey Edge Attention-based Multi-Relational Graph Convolutional Networks

Reference 88

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:26:24.884310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-12T01:07:43.805485Z digest=sha256:20c6d0d2b8735b4ccdad1bf8f020c21df9e23281a4714e0611e6706f16c9208a