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Paper Citation Record · LEDGER

GhostNet: More Features from Cheap Operations

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1911.11907.

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

pith.paper-citation-record.v1
1911.11907 v2

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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:32:57.655920Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T17:08:01.064064Z

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 30911187-5d9a-45ef-92d2-d480a3365ae5 · inbound

Finding Optimal Kernel Size and Dimension in Convolutional Neural Networks An Architecture Optimization Approach cites this paper.

Finding Optimal Kernel Size and Dimension in Convolutional Neural Networks An Architecture Optimization Approach GhostNet: More Features from Cheap Operations

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T00:32:57.655920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:32:57.655920Z digest=sha256:a8356d6cf79d611d194156e4599d6c34e2b7ff6da5d5e3200d4117ca4913e653

Observation c878e287-1c06-4cd4-8190-52b968796e96 · inbound

SARES-DEIM: Sparse Mixture-of-Experts Meets DETR for Robust SAR Ship Detection cites this paper.

SARES-DEIM: Sparse Mixture-of-Experts Meets DETR for Robust SAR Ship Detection GhostNet: More Features from Cheap Operations

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:08:01.065670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-13T17:03:04.479692Z digest=sha256:b41872cf381c50e5de3d92c8496aabbfde5e65dabe2c3fd01af210560f65f1d3