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Paper Citation Record · LEDGER

Survey on Graph Neural Network Acceleration: An Algorithmic Perspective

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2202.04822.

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

pith.paper-citation-record.v1
2202.04822 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:25:18.432377Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T20:43:15.385238Z

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 3bfa11da-f8c1-49f8-8f5b-73dbbf119edb · inbound

Inference-friendly Graph Compression for Graph Neural Networks cites this paper.

Inference-friendly Graph Compression for Graph Neural Networks Survey on Graph Neural Network Acceleration: An Algorithmic Perspective

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-16T12:25:18.432377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:25:18.432377Z digest=sha256:bcca296d6383ce1266ce034af67a6a7818db1cebd2c936e215947bb29237a4e7

Observation a26b3ef6-f4c5-4cca-b474-aeb54836b92b · inbound

Communication-free Sampling and 4D Hybrid Parallelism for Scalable Mini-batch GNN Training cites this paper.

Communication-free Sampling and 4D Hybrid Parallelism for Scalable Mini-batch GNN Training Survey on Graph Neural Network Acceleration: An Algorithmic Perspective

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-13T20:43:15.386711Z

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.

source=pdf_text observed=2026-05-13T20:38:31.444109Z digest=sha256:529359757f88902d67464eca11aed78723debe297b74e1cfb2e474faf69f5772