Paper Citation Record · LEDGER

Auto-GNN: Neural Architecture Search of Graph Neural Networks

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1909.03184.

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

pith.paper-citation-record.v1
1909.03184 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:38:09.388802Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-09T06:40:40.474257Z

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 56ade6b2-eef0-46ed-a6b0-190e6c916e28 · inbound

AutoML: A Survey of the State-of-the-Art cites this paper.

AutoML: A Survey of the State-of-the-Art Auto-GNN: Neural Architecture Search of Graph Neural Networks

Reference 278

Resolution: unresolved; no resolver link, observed 2026-08-14T15:38:09.388802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdd4420e-bb4f-474d-9a89-4b7a50e67fa6 · inbound

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search cites this paper.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Auto-GNN: Neural Architecture Search of Graph Neural Networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T23:48:48.494157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b32b9f0a-2aaf-46dd-a9c6-303952fcd5c4 · inbound

Automated Heterogeneous Network learning with Non-Recursive Message Passing cites this paper.

Automated Heterogeneous Network learning with Non-Recursive Message Passing Auto-GNN: Neural Architecture Search of Graph Neural Networks

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:54.410324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d67dfa80-9947-4c54-877e-e4fbe64eb643 · inbound

PARNESS: A Paper Harness for End-to-End Automated Scientific Research with Dynamic Workflows, Full-Text Indexing, and Cross-Run Knowledge Accumulation cites this paper.

PARNESS: A Paper Harness for End-to-End Automated Scientific Research with Dynamic Workflows, Full-Text Indexing, and Cross-Run Knowledge Accumulation Auto-GNN: Neural Architecture Search of Graph Neural Networks

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:40:40.476722Z

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.