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Paper Citation Record · LEDGER

Convolutional Self-Attention Networks

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1904.03107.

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

pith.paper-citation-record.v1
1904.03107 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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:50:07.530169Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T18:16:22.223912Z

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 0cc261af-b8f6-4093-b226-d1e008cbac37 · inbound

TPCNet: Representation learning for HI mapping cites this paper.

TPCNet: Representation learning for HI mapping Convolutional Self-Attention Networks

Reference 113

Resolution
metadata mismatch
local_arxiv, observed 2026-08-12T16:39:03.967146Z

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.

source=arxiv_source observed=2026-08-12T16:39:03.888671Z digest=sha256:442d714974793d671bc48b3163969bf38301d105034cbd17bb4c8f1a5ada651e

Observation e71c3a47-edda-494f-9eb8-8befbc374299 · inbound

Low-Resource Neural Machine Translation Using Recurrent Neural Networks and Transfer Learning: A Case Study on English-to-Igbo cites this paper.

Low-Resource Neural Machine Translation Using Recurrent Neural Networks and Transfer Learning: A Case Study on English-to-Igbo Convolutional Self-Attention Networks

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-16T10:50:07.530169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:50:07.530169Z digest=sha256:7c04a802487672b72908ce8df2217d7648ed3f0c2c5a2a45a7f08c2e7526d191