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Paper Citation Record · LEDGER

Quantum automated learning with provable and explainable trainability

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.05264.

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

pith.paper-citation-record.v1
2502.05264 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:48:51.457716Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T18:36:44.558461Z

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 96be196e-aa20-40a1-b973-ec8561ecf4d7 · inbound

Stochastic Quantum Hamiltonian Descent cites this paper.

Stochastic Quantum Hamiltonian Descent Quantum automated learning with provable and explainable trainability

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:51.457716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:51.457716Z digest=sha256:a8582c1cf186de932d0adb249fdd1f85d902e4ae9a997b8b1d259c7946d8468d

Observation da362e62-540e-4691-8d1f-96f8bed243c1 · inbound

A penalty-free quantum algorithm to find energy eigenstates cites this paper.

A penalty-free quantum algorithm to find energy eigenstates Quantum automated learning with provable and explainable trainability

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-18T18:36:44.560564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T18:33:03.416036Z digest=sha256:0ab6d49ec47f2be71a674c61b77c919ae9ed96eb37994457e1ff18556e707149