Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Trainability Enhancement of Parameterized Quantum Circuits via Reduced-Domain Parameter Initialization
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2302.06858.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T18:10:19.002192Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T22:05:49.997479Z
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 8a315e2b-712d-4cee-aa09-2a62c9568a81 · inbound
Quantum Convolutional Neural Networks are Effectively Classically Simulable cites this paper.
Quantum Convolutional Neural Networks are Effectively Classically Simulable Trainability Enhancement of Parameterized Quantum Circuits via Reduced-Domain Parameter Initialization
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T22:05:50.000384Z
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.
Observation ec252fac-716a-4e5f-b943-cf439cb65639 · inbound
Learning complexity gradually in quantum machine learning models cites this paper.
Learning complexity gradually in quantum machine learning models Trainability Enhancement of Parameterized Quantum Circuits via Reduced-Domain Parameter Initialization
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T18:10:19.002192Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 535ef9a3-7764-4693-870e-7bb3ad48eda2 · inbound
Q-MAML: Quantum Model-Agnostic Meta-Learning for Variational Quantum Algorithms cites this paper.
Q-MAML: Quantum Model-Agnostic Meta-Learning for Variational Quantum Algorithms Trainability Enhancement of Parameterized Quantum Circuits via Reduced-Domain Parameter Initialization
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:10:54.026013Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.