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Paper Citation Record · LEDGER

On establishing learning separations between classical and quantum machine learning with classical data

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2208.06339.

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

pith.paper-citation-record.v1
2208.06339 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 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:20:05.776147Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T05:50:41.014274Z

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 c3244e02-f65a-477c-bb22-9ef858f9904d · inbound

An unconditional distribution learning advantage with shallow quantum circuits cites this paper.

An unconditional distribution learning advantage with shallow quantum circuits On establishing learning separations between classical and quantum machine learning with classical data

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-12T14:20:05.776147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:20:05.776147Z digest=sha256:4198e721f7a0924c457663a0d3438290874097a8c83ae6035700528e9361a892

Observation 25685f24-6501-4740-ba42-6b65700f82ae · inbound

Artificial intelligence for representing and characterizing quantum systems cites this paper.

Artificial intelligence for representing and characterizing quantum systems On establishing learning separations between classical and quantum machine learning with classical data

Reference 112

Resolution
verified exact
local_arxiv, observed 2026-08-05T05:50:41.018999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T05:50:39.151876Z digest=sha256:4b86de798852dafe223dee13e8ba6f92f4d6049a0d0c44bab4dd2ef7b27afeb2