Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1808.10307.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T04:45:56.385353Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T20:03:56.976571Z
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 d3229100-ec5d-4aa2-8d1a-731254277dd7 · inbound
Invisible Backdoor Attacks on Deep Neural Networks via Steganography and Regularization cites this paper.
Invisible Backdoor Attacks on Deep Neural Networks via Steganography and Regularization Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T04:45:56.385353Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d82b4d8d-374a-4e84-8b27-50f6a59a38ec · inbound
MADE: Graph Backdoor Defense with Masked Unlearning cites this paper.
MADE: Graph Backdoor Defense with Masked Unlearning Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T11:48:09.514129Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f3832b6-7834-4c76-b478-1e4d1bee76c7 · inbound
An Effective and Resilient Backdoor Attack Framework against Deep Neural Networks and Vision Transformers cites this paper.
An Effective and Resilient Backdoor Attack Framework against Deep Neural Networks and Vision Transformers Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation
Reference 32
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T20:03:56.980363Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.