Pith. sign in

Paper Citation Record · LEDGER

Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1808.10307.

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

pith.paper-citation-record.v1
1808.10307 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 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:48:09.514129Z

measured 0 of 1 external citation measurements

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 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.

source=pdf_text observed=2026-08-12T11:48:09.514129Z digest=sha256:dd0d3e5b5ce91434126f2c8596ccc02992f019addd93e870d71af43581b71abb

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T20:03:56.740737Z digest=sha256:ec139cbe2fd81a952887fc68832f75cedfa71c5ba72ecd95d13fd4044b06b877