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Paper Citation Record · LEDGER

QC-Forest: a Classical-Quantum Algorithm to Provably Speedup Retraining of Random Forest

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.12008.

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

pith.paper-citation-record.v1
2406.12008 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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:20:28.592769Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T19:58:54.818723Z

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 e206d53c-7b4b-4171-8c2a-4e506ff4eb8e · inbound

Comprehensive Survey of QML: From Data Analysis to Algorithmic Advancements cites this paper.

Comprehensive Survey of QML: From Data Analysis to Algorithmic Advancements QC-Forest: a Classical-Quantum Algorithm to Provably Speedup Retraining of Random Forest

Reference 93

Resolution
verified exact
local_arxiv, observed 2026-08-10T19:58:54.823387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T19:58:51.376318Z digest=sha256:602ca5272c521b931174d4b30ae346a265b15b532b5cb530c8e562f125c25b70

Observation f09ca26d-ce74-406c-903b-780c016ac35f · inbound

A Quantum Bagging Algorithm with Unsupervised Base Learners for Label Corrupted Datasets cites this paper.

A Quantum Bagging Algorithm with Unsupervised Base Learners for Label Corrupted Datasets QC-Forest: a Classical-Quantum Algorithm to Provably Speedup Retraining of Random Forest

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-15T16:20:28.592769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:20:28.592769Z digest=sha256:b80aafda15f5e28cffdb579f8ca4558a0b0a1e084946715f4fb317e759d8c1c3