Pith. sign in

Paper Citation Record · LEDGER

Enhancing the Resilience of Graph Neural Networks to Topological Perturbations in Sparse Graphs

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.03097.

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

pith.paper-citation-record.v1
2406.03097 v1

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 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:30:56.128260Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T20:30:56.159774Z

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 402f5dff-87ba-4a98-9c1a-f61ea97ad525 · inbound

REGE: A Method for Incorporating Uncertainty in Graph Embeddings cites this paper.

REGE: A Method for Incorporating Uncertainty in Graph Embeddings Enhancing the Resilience of Graph Neural Networks to Topological Perturbations in Sparse Graphs

Reference 64

Resolution
verified exact
local_arxiv, observed 2026-08-11T20:30:56.164970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T20:30:56.128260Z digest=sha256:5ffc4f4b72c219c0341d94ff4bd420fad4ef1de3395380234f76b0cac9a3679d

Observation 42f74d63-8c7d-480d-86ee-98dc90892634 · inbound

Feature Space Topology Control via Hopkins Loss cites this paper.

Feature Space Topology Control via Hopkins Loss Enhancing the Resilience of Graph Neural Networks to Topological Perturbations in Sparse Graphs

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T17:04:16.472583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:04:16.472583Z digest=sha256:7414e132f786899911b3ceadf15d91fcc631b02af6bfde010e4c73bc03193705