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Paper Citation Record · LEDGER

GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1904.11492.

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

pith.paper-citation-record.v1
1904.11492 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 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T06:01:56.182716Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T06:01:56.378112Z

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 467fb78d-7f99-4ccd-bb48-ae798a58f8a8 · inbound

UPI-Net: Semantic Contour Detection in Placental Ultrasound cites this paper.

UPI-Net: Semantic Contour Detection in Placental Ultrasound GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-14T06:01:56.382677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-14T06:01:56.182716Z digest=sha256:010d1298659c8856a19267099980e2581fb958b8185ab3a6769d4110fc94e04f

Observation b9b928a1-4036-4af0-ba1c-c2cfd9299c01 · inbound

The Good, The Efficient and the Inductive Biases: Exploring Efficiency in Deep Learning Through the Use of Inductive Biases cites this paper.

The Good, The Efficient and the Inductive Biases: Exploring Efficiency in Deep Learning Through the Use of Inductive Biases GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T20:23:10.276979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:23:10.276979Z digest=sha256:1378a93d2b201cb211f896236a8230f39f56634a7db4dc656bfc23ad94a1269b