Paper Citation Record · LEDGER

Deep Graph Anomaly Detection: A Survey and New Perspectives

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 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 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:47:09.678165Z

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 ef151cfe-3983-42bf-9bd8-eb5c151b0c0a · inbound

TAD-Bench: A Comprehensive Benchmark for Embedding-Based Text Anomaly Detection cites this paper.

TAD-Bench: A Comprehensive Benchmark for Embedding-Based Text Anomaly Detection Deep Graph Anomaly Detection: A Survey and New Perspectives

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T17:47:09.678165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5388813d-b553-49ce-aa21-ba5e2805bfc7 · inbound

Bi-directional Curriculum Learning for Graph Anomaly Detection: Dual Focus on Homogeneity and Heterogeneity cites this paper.

Bi-directional Curriculum Learning for Graph Anomaly Detection: Dual Focus on Homogeneity and Heterogeneity Deep Graph Anomaly Detection: A Survey and New Perspectives

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T15:18:52.843323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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.

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.

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.

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 2026-08-20T06:33:59.587034+00:00.

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 2026-08-20T06:33:59.587034+00:00.

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 2026-08-20T06:33:59.587034+00:00.

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 2026-08-20T06:33:59.587034+00:00.