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Paper Citation Record · LEDGER

Spatially Focused Attack against Spatiotemporal Graph Neural Networks

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2109.04608.

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

pith.paper-citation-record.v1
2109.04608 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 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:18:54.942246Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T18:18:55.729000Z

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 3ca83676-101b-4bd6-8741-26e0ca6ce0f2 · inbound

Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting cites this paper.

Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting Spatially Focused Attack against Spatiotemporal Graph Neural Networks

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:18:55.737997Z

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.

source=arxiv_source observed=2026-08-11T18:18:54.942246Z digest=sha256:8dd60835ffeac88bcf3b186547da1cd56cf7c95f23fc48557f082b6ce3846781

Observation c13d2c8e-6d23-4770-9272-cb9dfdaa14ac · inbound

Revisiting the Adversarial Robustness of Graph-Based Traffic Forecasting cites this paper.

Revisiting the Adversarial Robustness of Graph-Based Traffic Forecasting Spatially Focused Attack against Spatiotemporal Graph Neural Networks

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-01T04:54:15.508196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T04:54:15.508196Z digest=sha256:9ebec326d03a5642ebc78260def79c91b52d5e22c996466f7e5ed39b9fa5a7a9