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Paper Citation Record · LEDGER

Neural Execution of Graph Algorithms

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1910.10593.

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

pith.paper-citation-record.v1
1910.10593 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:15:05.215316Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T02:39:30.005873Z

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 6e04143f-deb2-4990-983c-bb8f4e9f40eb · inbound

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges cites this paper.

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Execution of Graph Algorithms

Reference 96

Resolution
verified exact
arxiv_id, observed 2026-05-13T02:39:30.008473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T02:39:29.411021Z digest=sha256:105df5d05f72a23e5d80f29d7fa5362d841535c50210007cc5dd94c1dbced46d

Observation 6ac3bda0-e69a-4737-a227-273e1c5fae25 · inbound

FIGNN: Feature-Specific Interpretability for Graph Neural Network Surrogate Models cites this paper.

FIGNN: Feature-Specific Interpretability for Graph Neural Network Surrogate Models Neural Execution of Graph Algorithms

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T04:15:05.215316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:05.215316Z digest=sha256:8dc5997ae5f0bd288201e73ac0866c0cc7d78320a24088f290e09b2144479581

Observation 715fdf33-ec7a-4edc-b6e1-71449d6976de · inbound

Distance-Preserving Embeddings in Inhomogeneous Random Graphs cites this paper.

Distance-Preserving Embeddings in Inhomogeneous Random Graphs Neural Execution of Graph Algorithms

Reference 182

Resolution
unresolved
no resolver link, observed 2026-07-14T00:37:04.989965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T00:37:04.989965Z digest=sha256:bec60083befb99c5acb2968ed085ee33b7c802fcbe788244ca45410a7ceee189