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Paper Citation Record · LEDGER

Non-native Quantum Generative Optimization with Adversarial Autoencoders

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.13830.

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

pith.paper-citation-record.v1
2407.13830 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:02:41.481713Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:29:59.799628Z

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 638ca521-c405-4564-bbc4-6254d85ddc38 · inbound

Machine-Learning-Assisted Photonic Device Development: A Multiscale Approach from Theory to Characterization cites this paper.

Machine-Learning-Assisted Photonic Device Development: A Multiscale Approach from Theory to Characterization Non-native Quantum Generative Optimization with Adversarial Autoencoders

Reference 114

Resolution
unresolved
no resolver link, observed 2026-08-06T23:02:41.481713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:02:41.481713Z digest=sha256:0ec7604ecb35183359496cd3a839c52555e9d57fa1db20fa78ed5c33a2bb82b3

Observation adddd746-0f55-44ac-9909-e2af2342916e · inbound

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers cites this paper.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Non-native Quantum Generative Optimization with Adversarial Autoencoders

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:29:59.949459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:29:59.534826Z digest=sha256:2946e0ca0bee27458242933589bdbbc0eec5a7c1e1014fffe7b74f15f3725f6d