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Paper Citation Record · LEDGER

Trade-off between Gradient Measurement Efficiency and Expressivity in Deep Quantum Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.18316.

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

pith.paper-citation-record.v1
2406.18316 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T07:06:53.439022Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T20:33:25.724356Z

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 04ac2c44-ee98-4ffc-810f-d4c7769f2e09 · inbound

Resource-efficient equivariant quantum convolutional neural networks cites this paper.

Resource-efficient equivariant quantum convolutional neural networks Trade-off between Gradient Measurement Efficiency and Expressivity in Deep Quantum Neural Networks

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-23T20:33:25.726560Z

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=2026-05-23T20:30:57.645894Z digest=sha256:c50d4f0e56ffa61a7bb8114bc09bddedaa6430fa4d2172e8e1645c37d1fba266

Observation 106c02f8-a30c-49d4-825a-b74ffcfd0e22 · inbound

When cheap gradients fail: the measurement cost of attacking quantum classifiers cites this paper.

When cheap gradients fail: the measurement cost of attacking quantum classifiers Trade-off between Gradient Measurement Efficiency and Expressivity in Deep Quantum Neural Networks

Reference 31

Resolution
unresolved
no resolver link, observed 2026-07-14T07:06:53.439022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T07:06:53.439022Z digest=sha256:fac1a72c0fa70db5e8d2189e4bd6b0f1b85058a4383d4b00bb73adc2fd7f2b72