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Paper Citation Record · LEDGER

Hybrid Quantum-Classical Feature Extraction approach for Image Classification using Autoencoders and Quantum SVMs

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.18814.

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

pith.paper-citation-record.v1
2410.18814 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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T18:10:58.831681Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 0395e16c-7431-4d9a-8ac5-d49bf6c0329a · inbound

Quantum kernel and HHL-based support vector machines for multi-class classification cites this paper.

Quantum kernel and HHL-based support vector machines for multi-class classification Hybrid Quantum-Classical Feature Extraction approach for Image Classification using Autoencoders and Quantum SVMs

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-04T18:10:58.831681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:10:58.831681Z digest=sha256:c132f57f3fec44ec9bae592616df6242cdc197c348c4ffa183c83d99107cb0f9

Observation c3454e68-ad84-4808-8ec0-f6b9bc941802 · inbound

Machine learning development for quantum computing and neutrino physics cites this paper.

Machine learning development for quantum computing and neutrino physics Hybrid Quantum-Classical Feature Extraction approach for Image Classification using Autoencoders and Quantum SVMs

Reference 106

Resolution
unresolved
no resolver link, observed 2026-08-02T04:31:51.542743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T04:31:51.542743Z digest=sha256:ffdb4a0940332e8a327857abacc686448f494a34867635d4c483ef7e653489cd