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Paper Citation Record · LEDGER

What can we learn from quantum convolutional neural networks?

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2308.16664.

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

pith.paper-citation-record.v1
2308.16664 v3

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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:10:19.114827Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T15:25:31.170887Z

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 fb3c4bdf-3ec8-4321-81fe-4bc19f5cfeac · inbound

Learning complexity gradually in quantum machine learning models cites this paper.

Learning complexity gradually in quantum machine learning models What can we learn from quantum convolutional neural networks?

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-12T18:10:19.114827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:10:19.114827Z digest=sha256:d69855c096cc45263f73f509c87f35e9c64cb68915e6fdfd0581cff9590bc812

Observation 4b8aa73a-165f-4922-ba89-521ad41d4f07 · inbound

Addressing the Readout Problem in Quantum Differential Equation Algorithms with Quantum Scientific Machine Learning cites this paper.

Addressing the Readout Problem in Quantum Differential Equation Algorithms with Quantum Scientific Machine Learning What can we learn from quantum convolutional neural networks?

Reference 93

Resolution
verified exact
local_arxiv, observed 2026-08-12T15:25:31.175022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:25:30.660846Z digest=sha256:35b8d3fada14f88b310bfc77526ee5135157db927de4be79685c308ef7cc6c8c