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Paper Citation Record · LEDGER

Deep Graph Anomaly Detection: A Survey and New Perspectives

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2409.09957.

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

pith.paper-citation-record.v1
2409.09957 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:13:55.103929Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T23:41:54.612973Z

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 b9703050-3b2e-4419-b56e-95d12ac20303 · inbound

AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection cites this paper.

AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection Deep Graph Anomaly Detection: A Survey and New Perspectives

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T22:13:55.103929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:13:55.103929Z digest=sha256:aea5f48fcaeb4833b63272af92e4041c6344a4b9ef278a14766efa23ac6f9327

Observation 66f8178a-8225-41ae-babf-06d0d3dd1a57 · inbound

Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening cites this paper.

Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening Deep Graph Anomaly Detection: A Survey and New Perspectives

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-07T15:43:17.600541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:43:17.600541Z digest=sha256:b7296a72d7b2d0b3707e1c5a872f7dd32534b1f4f7c4bf98c5e918bb68e4da34

Observation 32f4b180-f196-425a-80ae-1e06ebcf3d65 · inbound

Learnable Kernel Density Estimation for Graphs and Its Application to Graph-Level Anomaly Detection cites this paper.

Learnable Kernel Density Estimation for Graphs and Its Application to Graph-Level Anomaly Detection Deep Graph Anomaly Detection: A Survey and New Perspectives

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T13:43:15.476064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:43:15.476064Z digest=sha256:8bb35f90a8b5fa132a02f82bd2c154c2b05e9d676a010a36fc7a57f6da885679

Observation 85a95290-8745-4e77-b934-5bb9282b383c · inbound

Synergizing LLMs with Global Label Propagation for Multimodal Fake News Detection cites this paper.

Synergizing LLMs with Global Label Propagation for Multimodal Fake News Detection Deep Graph Anomaly Detection: A Survey and New Perspectives

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T12:09:42.468085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:42.468085Z digest=sha256:349c6d85c53b7bba21888a4626a36b332c01a735be901b8b80730cf7e44ecb49

Observation 7853ecbb-e845-4d57-8efe-a91982148672 · inbound

BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks cites this paper.

BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks Deep Graph Anomaly Detection: A Survey and New Perspectives

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-18T23:41:54.617015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T23:38:10.078340Z digest=sha256:bfb9f91f1f37077e651fd568f829565914e37d5529746eecd721ea192b8fdbb6

Observation 95da6057-c3dc-42c0-b6ca-86477aa38ad1 · inbound

NK-GAD: Neighbor Knowledge-Enhanced Unsupervised Graph Anomaly Detection cites this paper.

NK-GAD: Neighbor Knowledge-Enhanced Unsupervised Graph Anomaly Detection Deep Graph Anomaly Detection: A Survey and New Perspectives

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:08:25.499594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T09:08:10.024550Z digest=sha256:8d41d4d51fa2d27acf4606b3c489667255f53f093274af3e022a1bb2a18697a4

Observation b4630bce-54b6-45c8-a7e6-2baa6aebca5b · inbound

When Normality Shifts: Risk-Aware Test-Time Adaptation for Unsupervised Tabular Anomaly Detection cites this paper.

When Normality Shifts: Risk-Aware Test-Time Adaptation for Unsupervised Tabular Anomaly Detection Deep Graph Anomaly Detection: A Survey and New Perspectives

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T05:26:25.402341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T05:21:40.243903Z digest=sha256:187e30a53f2333fdb8a13f18826db4cd464040f614e348c32641ec63d77a8456

Observation 2eed8ace-f913-44d7-8de3-26a3d99c4dff · inbound

Learning Feature Encoder with Synthetic Anomalies for Weakly Supervised Graph Anomaly Detection cites this paper.

Learning Feature Encoder with Synthetic Anomalies for Weakly Supervised Graph Anomaly Detection Deep Graph Anomaly Detection: A Survey and New Perspectives

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T06:32:24.552602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T06:29:31.837409Z digest=sha256:2225750a3d72ab89139c93d2cf1f48aa7319e834fa7000fb399d299c5df5dfbf