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Paper Citation Record · LEDGER

Applications of Quantum Machine Learning for Quantitative Finance

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.10119.

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

pith.paper-citation-record.v1
2405.10119 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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:25:30.349724Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T22:30:22.166745Z

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 4416feef-37ab-4a49-9068-4f3f12edd215 · inbound

Addressing the Readout Problem in Quantum Differential Equation Algorithms with Quantum Scientific Machine Learning cites this paper.

Addressing the Readout Problem in Quantum Differential Equation Algorithms with Quantum Scientific Machine Learning Applications of Quantum Machine Learning for Quantitative Finance

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T15:25:30.349724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:25:30.349724Z digest=sha256:711492782c6dba8bdcdd8559c0646ee33d2f06c6ce513a8e80f8fecd327d0176

Observation d9995af7-cb34-4974-9379-94210c5d234d · inbound

A Quantum Reservoir Computing Approach to Quantum Stock Movement Forecasting in Quantum-Invested Markets cites this paper.

A Quantum Reservoir Computing Approach to Quantum Stock Movement Forecasting in Quantum-Invested Markets Applications of Quantum Machine Learning for Quantitative Finance

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-15T22:30:22.170050Z

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=2026-05-15T22:27:38.431667Z digest=sha256:e15e29ab706e5b712bcc5a9a416637d080fec457bfbd5a5e0f4d5e04466e87e8