Paper Citation Record · LEDGER

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2501.14959.

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

pith.paper-citation-record.v1
2501.14959 v2

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 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:56:03.061788Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T03:22:12.861565Z

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 8afd8f34-bfd4-4e67-abc9-ff114f641fd3 · inbound

Semivalue-based data valuation is arbitrary and gameable cites this paper.

Semivalue-based data valuation is arbitrary and gameable Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T00:56:03.061788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2cc060a8-91a8-4d8d-aff4-3ba221198c28 · inbound

Argumentative Ensembling for Robust Recourse under Model Multiplicity cites this paper.

Argumentative Ensembling for Robust Recourse under Model Multiplicity Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T23:04:23.495364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72e6fe20-b148-4f81-8244-60fc98d8c4cd · inbound

Exploring the Rashomon Set for Concept-Based Models cites this paper.

Exploring the Rashomon Set for Concept-Based Models Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:48.646440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db143ab5-4ede-490e-8fed-45756f0c0246 · inbound

Rashomon Sets and Model Multiplicity in Federated Learning cites this paper.

Rashomon Sets and Model Multiplicity in Federated Learning Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-16T03:22:12.865981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8e90813c-e3a7-4ea1-9b45-320e1a44cb9f · inbound

An empirical evaluation of the risks of AI model updates using clinical data: stability, arbitrariness, and fairness cites this paper.

An empirical evaluation of the risks of AI model updates using clinical data: stability, arbitrariness, and fairness Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:33.223698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.