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Paper Citation Record · LEDGER

Bit-bit encoding, optimizer-free training and sub-net initialization: techniques for scalable quantum machine learning

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2501.02148.

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

pith.paper-citation-record.v1
2501.02148 v2

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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:17:38.451063Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T00:23:29.291851Z

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 b05c9a91-95f4-40c5-8d16-842358001c0c · inbound

A Quantum Platform for Multiomics Data cites this paper.

A Quantum Platform for Multiomics Data Bit-bit encoding, optimizer-free training and sub-net initialization: techniques for scalable quantum machine learning

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:23:29.396292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T00:23:25.785823Z digest=sha256:9efd29111496fb5a7140368adf8f29401891d14881eb6b5a29165b9d878fa0b4

Observation 74328f53-c095-42f0-b8cb-2524ae177c30 · inbound

Benchmarking Quantum and Classical Machine Learning Models on Oncological Data cites this paper.

Benchmarking Quantum and Classical Machine Learning Models on Oncological Data Bit-bit encoding, optimizer-free training and sub-net initialization: techniques for scalable quantum machine learning

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T14:17:38.451063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:17:38.451063Z digest=sha256:90d176a1b1abecc7d9be4235e5337604dd829aeffd93779f1672acdf24619497