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Paper Citation Record · LEDGER

Analysis of quantum neural network performance via edge cases

As of 8 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2506.12427.

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

pith.paper-citation-record.v1
2506.12427 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:56:19.810111Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

  • verified exact4
  • verified fuzzy4
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 062ee252-1190-4eaa-9697-2212f8880f50 · outbound

This paper cites PennyLane: Automatic differentiation of hybrid quantum-classical computations.

Analysis of quantum neural network performance via edge cases PennyLane: Automatic differentiation of hybrid quantum-classical computations

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:18.655513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:18.655513Z digest=sha256:3000c23ba03fa259fe756ab3add4a870b56ed8aad5528e58203697bd3d0a8ff0

Observation 2a7b44fe-e0c3-459b-b894-3e7087a90cb3 · outbound

This paper cites Learning surrogate models for simulation-based optimization,.

Analysis of quantum neural network performance via edge cases Learning surrogate models for simulation-based optimization,

Reference 2

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unresolved
no resolver link, observed 2026-08-07T00:56:18.716022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:18.716022Z digest=sha256:cfe3158bbfcb3aa05cb1a994d2428e44d808d8731a9ffbf86b6b6daae531015a

Observation 82e49996-8500-4a87-97ca-b53929f9a09a · outbound

This paper cites Performance evaluation of different machine learning techniques for prediction of heart disease,.

Analysis of quantum neural network performance via edge cases Performance evaluation of different machine learning techniques for prediction of heart disease,

Reference 3

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verified exact
doi, observed 2026-08-07T00:56:20.436709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 06cbf7fa-68bb-4e37-9889-828c845b2938 · outbound

This paper cites On random graphs. I.

Analysis of quantum neural network performance via edge cases On random graphs. I

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:56:21.854498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:56:18.869525Z digest=sha256:3343af02e6d9f39302381f2036deeaa881c7a0d5ab12b7a0f67cf1b6e5e117f7

Observation f3600e78-8277-4f24-8f9e-f5cf237bbffe · outbound

This paper cites Performance Evaluation in Machine Learning: The Good, the Bad, the Ugly, and the Way Forward,.

Analysis of quantum neural network performance via edge cases Performance Evaluation in Machine Learning: The Good, the Bad, the Ugly, and the Way Forward,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:56:21.611066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:56:18.968354Z digest=sha256:7e8daa0707b34bc231318bb7b9c937aa69e4039d7352a24c6d54094493e2f241

Observation 2100e82f-f6a5-4adf-b6e6-8378ff2e21f7 · outbound

This paper cites Performance Evaluation in Machine Learning,.

Analysis of quantum neural network performance via edge cases Performance Evaluation in Machine Learning,

Reference 6

Resolution
verified exact
doi, observed 2026-08-07T00:56:20.208751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:56:19.085746Z digest=sha256:44e08c69ffc5a3ae256721df2fe295043f49231cb1282d5a9d0fa3789303aace

Observation 1387093a-c641-42db-bad2-ce50b7c84421 · outbound

This paper cites Performance measures in evaluating machine learning based bioinformatics predictors for classifications,.

Analysis of quantum neural network performance via edge cases Performance measures in evaluating machine learning based bioinformatics predictors for classifications,

Reference 7

Resolution
verified exact
doi, observed 2026-08-07T00:56:20.070689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:56:19.168261Z digest=sha256:2a5c3329bf92803fa5759ff8c9fadb9fb186cdbfc7382671fbd6267c4a5ecfec

Observation 8c8173d4-8341-44f9-bc1d-4afc5becd755 · outbound

This paper cites Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques,.

Analysis of quantum neural network performance via edge cases Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:56:21.377067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:56:19.262165Z digest=sha256:3a47cfcc5e2d9cdabbaa2da1e67630b9f8e0cbe5bec6e98ceb1a305aea3a76a5

Observation 87a2db32-3e9b-486f-8027-c113b6ff3759 · outbound

This paper cites Permutation-invariant quantum circuits.

Analysis of quantum neural network performance via edge cases Permutation-invariant quantum circuits

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:19.351693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:19.351693Z digest=sha256:2c587a83e32d3ea3b5cbd89b9f2373960ab2490839daee0a158f0d7c4425ba8d

Observation 19537e63-1db5-4a61-b3b8-1b372ed8fe4d · outbound

This paper cites Scaling of symmetry-restricted quantum circuits.

Analysis of quantum neural network performance via edge cases Scaling of symmetry-restricted quantum circuits

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:19.406110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:19.406110Z digest=sha256:e4227998d8c9bf7cb2d282c78cbdab21edc507ceeaa83383db0aa3ed9f5e1929

Observation f4b28ae2-fad4-453f-8f41-4cb06e248e1f · outbound

This paper cites Solving graph problems using permutation-invariant quantum machine learning.

Analysis of quantum neural network performance via edge cases Solving graph problems using permutation-invariant quantum machine learning

Reference 11

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verified exact
local_arxiv, observed 2026-08-07T00:56:20.676969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 64f1fde5-05dc-4b58-adcf-c4a49108949f · outbound

This paper cites A Review of Evaluation Metrics in Machine Learning Algorithms,.

Analysis of quantum neural network performance via edge cases A Review of Evaluation Metrics in Machine Learning Algorithms,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:19.630070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:19.630070Z digest=sha256:1dc750812feec9dbdfce8f4f5a18968c9d52cdf4c1f3afaf61e63b9e0d85e523

Observation 8e3344fe-8693-47c1-95a5-4708fff7f3be · outbound

This paper cites Machine learning and uncertainty quantification for surrogate models of integrated devices with a large number of parameters,.

Analysis of quantum neural network performance via edge cases Machine learning and uncertainty quantification for surrogate models of integrated devices with a large number of parameters,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:56:21.050670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:56:19.718668Z digest=sha256:732945eb5c675c79a165cbced2fff4f0487fb4b798cf988d73ecff33380e37cd

Observation 7a9aed22-f766-4e11-9511-8e3bd6c0246a · outbound

This paper cites Evaluating Machine Learning Models and Their Diagnostic Value,.

Analysis of quantum neural network performance via edge cases Evaluating Machine Learning Models and Their Diagnostic Value,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:19.810111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:19.810111Z digest=sha256:ade521b9e484e4903de6243bbc71c2b5fa7bf1ca71b33881b32a853634d7c79d

Pith citing papers

No inbound Pith citation observations are available.