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Paper Citation Record · LEDGER

Machine learning and invariant theory

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2209.14991.

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

pith.paper-citation-record.v1
2209.14991 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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:29:56.296770Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T21:36:16.933265Z

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 7a2a8008-4264-4fdf-928c-c5da290d7434 · inbound

Lie-Equivariant Quantum Graph Neural Networks cites this paper.

Lie-Equivariant Quantum Graph Neural Networks Machine learning and invariant theory

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-12T14:29:56.296770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:29:56.296770Z digest=sha256:b2f6b16d3ea519a758e11089000b392c58c61a4d11bf79440f788d06ae361bf7

Observation 56e5aa18-1d4c-48a3-8458-fdf1a84bad8b · inbound

Risk-Controlled Post-Processing of Decision Policies cites this paper.

Risk-Controlled Post-Processing of Decision Policies Machine learning and invariant theory

Reference 269

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:36:16.936190Z

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=arxiv_source observed=2026-05-08T04:49:25.540705Z digest=sha256:fffa45823a935873009199e6b7d7779cba34492d25129f2f2bcfbe5d384c2706