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Paper Citation Record · LEDGER

Quantum Machine Learning Architecture Search via Deep Reinforcement Learning

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.20147.

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

pith.paper-citation-record.v1
2407.20147 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 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:44:29.264565Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T14:06:45.598101Z

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 46cbb313-ea22-4b47-bdd8-8d2ae47ca216 · inbound

Quantum Machine Learning: An Interplay Between Quantum Computing and Machine Learning cites this paper.

Quantum Machine Learning: An Interplay Between Quantum Computing and Machine Learning Quantum Machine Learning Architecture Search via Deep Reinforcement Learning

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-12T20:44:29.264565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:44:29.264565Z digest=sha256:951eaf0790cd75daa4fb43c90fbb8cef81b548fe204539551853ea25a417570f

Observation ab2f3a2c-8116-4b84-92f3-6ed395aacbcb · inbound

Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacity cites this paper.

Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacity Quantum Machine Learning Architecture Search via Deep Reinforcement Learning

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-11T14:06:45.604797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:06:45.448489Z digest=sha256:bb2c07958dcb3a5ff9da33df1483bb3f26f6896ecac90c3f9bc8de5dd2d065eb