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Paper Citation Record · LEDGER

Deep-Q Learning with Hybrid Quantum Neural Network on Solving Maze Problems

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2304.10159.

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

pith.paper-citation-record.v1
2304.10159 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 2026-08-10T19:05:54.468852Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T04:33:57.736155Z

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 fabd85e2-b03c-49e1-8bf7-863baf045285 · inbound

Hybrid-Quantum Neural Architecture Search for The Proximal Policy Optimization Algorithm cites this paper.

Hybrid-Quantum Neural Architecture Search for The Proximal Policy Optimization Algorithm Deep-Q Learning with Hybrid Quantum Neural Network on Solving Maze Problems

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-10T19:05:54.468852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:05:54.468852Z digest=sha256:4e408c403da0d9b7f4e036e4d52f256e109de7b109091abdf0151fb33c400005

Observation 04dc8123-74fb-4b49-a881-a48dfbd4d962 · inbound

Enhanced Reinforcement Learning-based Process Synthesis via Quantum Computing cites this paper.

Enhanced Reinforcement Learning-based Process Synthesis via Quantum Computing Deep-Q Learning with Hybrid Quantum Neural Network on Solving Maze Problems

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-21T04:33:57.737995Z

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=2026-05-21T04:33:26.629494Z digest=sha256:34cb05711bc53b03b7d94297cef786d86563d0e754c05cefb512ac4e3a71edcd