Paper Citation Record · LEDGER

Robustness Inspired Graph Backdoor Defense

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.09836.

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

pith.paper-citation-record.v1
2406.09836 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:53:48.261424Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:19:47.742498Z

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 7b762d39-13e4-4642-ab52-239f76b0bf7f · inbound

Stealing Training Graphs from Graph Neural Networks cites this paper.

Stealing Training Graphs from Graph Neural Networks Robustness Inspired Graph Backdoor Defense

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-12T18:53:48.261424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8a489fd-a5fb-460b-8119-85f336052b43 · inbound

Fine-tuning is Not Fine: Mitigating Backdoor Attacks in GNNs with Limited Clean Data cites this paper.

Fine-tuning is Not Fine: Mitigating Backdoor Attacks in GNNs with Limited Clean Data Robustness Inspired Graph Backdoor Defense

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:32.839839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcd5e8d2-fc32-43c9-a297-82707052d6e1 · inbound

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective cites this paper.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Robustness Inspired Graph Backdoor Defense

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:30.030370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04d2a548-8726-4a9a-9bf6-60e76d80b0ec · inbound

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers cites this paper.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Robustness Inspired Graph Backdoor Defense

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:23.415746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5e854dda-fdc2-4224-a785-1916b84be309 · inbound

Rethinking Molecular Graph Backdoors under Chemistry-aware Admission cites this paper.

Rethinking Molecular Graph Backdoors under Chemistry-aware Admission Robustness Inspired Graph Backdoor Defense

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:19:47.743910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.