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Paper Citation Record · LEDGER

Contextuality and inductive bias in quantum machine learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2302.01365.

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

pith.paper-citation-record.v1
2302.01365 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:53:40.586220Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T13:17:55.014771Z

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 bd190a88-a7b6-431a-92a9-4d0c0a252ff3 · inbound

Is data-efficient learning feasible with quantum models? cites this paper.

Is data-efficient learning feasible with quantum models? Contextuality and inductive bias in quantum machine learning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:40.586220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:40.586220Z digest=sha256:71100dac61bb4424b2b3de2ecf02ceee67b02e4105395fb251cbc90d28384631

Observation e4ab17f6-ae54-45e9-8c26-23d5484c2c3c · inbound

Typicality of Contextuality cites this paper.

Typicality of Contextuality Contextuality and inductive bias in quantum machine learning

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-04T08:31:44.831123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:31:44.831123Z digest=sha256:7f0396a73f7aafc775988b6e0ff12bad47d37b42fad8e0d98a0aa1e79b8ea28d

Observation 2f2733c9-a012-456d-a5e5-9c9fecfe1b04 · inbound

Geometric Preconditioning and Curriculum Optimization for Trainable Variational Quantum Regression cites this paper.

Geometric Preconditioning and Curriculum Optimization for Trainable Variational Quantum Regression Contextuality and inductive bias in quantum machine learning

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-16T13:17:55.018017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T13:13:55.126977Z digest=sha256:a32932d9e0d28d6abec2efed89d67f37c943eb79371f7120fc33124a7a443bde

Observation be71b7fe-5916-49b3-b7ab-cb8617d2b078 · inbound

Quantum Machine Learning for Colorectal Cancer Data: Anastomotic Leak Classification and Risk Factors cites this paper.

Quantum Machine Learning for Colorectal Cancer Data: Anastomotic Leak Classification and Risk Factors Contextuality and inductive bias in quantum machine learning

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T13:05:24.639805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T13:04:10.261590Z digest=sha256:a42ab5aa8bba2e33c9e14bade9c015fc8629779dd1c713af0ad57d625f8e8fc3

Observation 1b877b5a-1b05-406a-98eb-9ed42dd42068 · inbound

The power of entanglement in distributed quantum machine learning cites this paper.

The power of entanglement in distributed quantum machine learning Contextuality and inductive bias in quantum machine learning

Reference 36

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T10:41:31.421281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-07T04:05:55.899901Z digest=sha256:bf78f039c03bfe081900c5a2f74bf1c2e2db1b815cf376f147d29a295aad8e79