Paper Citation Record · LEDGER

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning

As of 10 August 2026, this Paper Citation Record lists 22 of 22 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 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:49:40.301757Z

measured 27 of 27 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 2026-08-07T00:56:03.061788Z

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

22 of 22 outbound references displayed

verified exact1
verified fuzzy10
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b9b63708-b7b0-426c-9136-642535a3da95 · outbound

This paper cites Details of the search are provided in §A.1.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Details of the search are provided in §A.1

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:49:40.477463Z

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.

Observation 573c6e58-cf94-487c-862d-140fc366bbf2 · outbound

This paper cites The exact inclusion criteria are noted in §A.2.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning The exact inclusion criteria are noted in §A.2

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:49:40.467571Z

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.

Observation c21f0640-6c03-4f90-90cb-4c90587a7361 · outbound

This paper cites Georgetown Law Journal, 113(1).

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Georgetown Law Journal, 113(1)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:49:40.532823Z

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.

Observation afa4d919-1ca3-44c2-8e93-13a8695f6771 · outbound

This paper cites In The Thirty-eighth Annual Conference on Neu- ral Information Processing Systems.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning In The Thirty-eighth Annual Conference on Neu- ral Information Processing Systems

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:49:40.521840Z

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.

Observation ba3b6e41-0073-47ff-993a-96f97e876229 · outbound

This paper cites On the Rashomon ratio of infinite hypothesis sets.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning On the Rashomon ratio of infinite hypothesis sets

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:49:40.429446Z

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.

Observation f24ef7b9-2b72-4cf7-81e7-fb3f0fe4bc37 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Explaining and Harnessing Adversarial Examples

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T14:49:40.251873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7691ac0-f071-4b07-b3a0-6a72ddac2ae3 · outbound

This paper cites Can we Agree? On the Rash\=omon Effect and the Reliability of Post-Hoc Explainable AI.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Can we Agree? On the Rash\=omon Effect and the Reliability of Post-Hoc Explainable AI

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T14:49:40.278069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 384b7469-c85d-4fc2-a991-760cd0c0b1ab · outbound

This paper cites Amazing Things Come From Having Many Good Models.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Amazing Things Come From Having Many Good Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T14:49:40.282193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae934946-f182-461c-b2be-2751fd7e607e · outbound

This paper cites X Hacking: The Threat of Misguided AutoML.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning X Hacking: The Threat of Misguided AutoML

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T14:49:40.286234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81233556-f12b-4d9d-a309-e3acaae1088e · outbound

This paper cites Predictive Churn with the Set of Good Models.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Predictive Churn with the Set of Good Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T14:49:40.290264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47a2d609-b3cd-4bb6-a947-23dc52e1cc0a · outbound

This paper cites The set of tags used and categoriza- tion rules are discussed in §A.3.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning The set of tags used and categoriza- tion rules are discussed in §A.3

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:49:40.456829Z

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.

Observation d839ab9b-ad88-415a-91f6-4ab49d019cc3 · outbound

This paper cites Bertsekas, D.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Bertsekas, D

Reference 418

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:49:40.541607Z

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.

Observation 3a9baa94-d816-4c82-a85d-b67293e28921 · outbound

This paper cites Pansky, A.; Koriat, A.; and Goldsmith, M.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Pansky, A.; Koriat, A.; and Goldsmith, M

Reference 554

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:49:40.488827Z

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.

Observation b90c0aae-1522-42d9-a33b-eb7f537e8006 · outbound

This paper cites Practical Attribution Guidance for Rashomon Sets.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Practical Attribution Guidance for Rashomon Sets

Reference 808

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:49:40.406538Z

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.

Observation deef6ad2-3be2-4ed1-ab1c-818200ffda6f · outbound

This paper cites Torch.manual_seed(3407) is all you need: On the influence of random seeds in deep learning architectures for computer vision.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Torch.manual_seed(3407) is all you need: On the influence of random seeds in deep learning architectures for computer vision

Reference 818

Resolution: unresolved; no resolver link, observed 2026-08-10T14:49:40.274067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 942c9e01-3280-4c9d-98a2-29646a004461 · outbound

This paper cites An Experimental Study on the Rashomon Effect of Balancing Methods in Imbalanced Classification.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning An Experimental Study on the Rashomon Effect of Balancing Methods in Imbalanced Classification

Reference 2008

Resolution: unresolved; no resolver link, observed 2026-08-10T14:49:40.239255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82ee1030-4a96-46c3-b4fd-43938fff194d · outbound

This paper cites Accounting for multiplicity in machine learning benchmark performance.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Accounting for multiplicity in machine learning benchmark performance

Reference 2016

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:49:40.380159Z

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.

Observation 700681a1-6d9a-4742-bb7f-9123e66da45a · outbound

This paper cites Biosystems engineering, 170: 51–60.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Biosystems engineering, 170: 51–60

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:49:40.510311Z

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.

Observation bd824077-82dd-4e86-a91d-5754ed598261 · outbound

This paper cites On Evaluating Adversarial Robustness.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning On Evaluating Adversarial Robustness

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T14:49:40.234808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d99a3066-ffb6-4ae6-9ed9-6785e1cdb82b · outbound

This paper cites Perceptions of the Fairness Impacts of Multiplicity in Machine Learning.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Perceptions of the Fairness Impacts of Multiplicity in Machine Learning

Reference 2022

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:49:40.393456Z

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.

Observation a8ab5367-bf56-446c-ac05-b587327d39b7 · outbound

This paper cites In Proceedings of the 2023 ACM Confer- ence on Fairness, Accountability, and Transparency, 1609– 1623.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning In Proceedings of the 2023 ACM Confer- ence on Fairness, Accountability, and Transparency, 1609– 1623

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:49:40.499007Z

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.

Observation d09551df-6124-4a03-944d-9c1732ce2114 · outbound

This paper cites Political Science Research and Methods, 12(4): 841–848.

Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning Political Science Research and Methods, 12(4): 841–848

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:49:40.552758Z

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.

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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+00:00.