Paper Citation Record · LEDGER

MOSS: Multi-Objective Optimization for Stable Rule Sets

As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2506.08030.

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

pith.paper-citation-record.v1
2506.08030 v2

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:53:58.903434Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

verified exact0
verified fuzzy24
unresolved13
parse uncertain1
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a217f950-7298-4520-8cea-1bc189357ca2 · outbound

This paper cites Version 9.0.,.

MOSS: Multi-Objective Optimization for Stable Rule Sets Version 9.0.,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:05.423181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2a689946-7005-4291-a4c0-3a70fd2315de · outbound

This paper cites an unresolved cited work.

MOSS: Multi-Objective Optimization for Stable Rule Sets Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:54:05.015918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8e59ae46-bd16-49dd-bb15-db49c5c88696 · outbound

This paper cites Sirus: Stable and interpretable rule set for classification.Electronic Journal of Statistics, 15:427–505, 2021.

MOSS: Multi-Objective Optimization for Stable Rule Sets Sirus: Stable and interpretable rule set for classification.Electronic Journal of Statistics, 15:427–505, 2021

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:04.836659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9867da6f-9ace-4da1-9912-6a9a19cc3bca · outbound

This paper cites Sparse high-dimensional regression.The Annals of Statistics, 48(1):300–323, 2020.

MOSS: Multi-Objective Optimization for Stable Rule Sets Sparse high-dimensional regression.The Annals of Statistics, 48(1):300–323, 2020

Reference 4

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Source-reported events for the cited work

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Observation a7548cf0-143f-454a-a9b9-e0de8817b891 · outbound

This paper cites Sparse classification: a scalable discrete optimization perspective.Machine Learning, 110:3177–3209, 2021.

MOSS: Multi-Objective Optimization for Stable Rule Sets Sparse classification: a scalable discrete optimization perspective.Machine Learning, 110:3177–3209, 2021

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:04.575897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 288f57a3-9724-4163-95e1-283d17864965 · outbound

This paper cites Cambridge university press, 2004.

MOSS: Multi-Objective Optimization for Stable Rule Sets Cambridge university press, 2004

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T11:53:56.034806Z

Source-reported events for the cited work

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Observation 10d9b23d-8075-4e50-88a2-6c37fb3172cc · outbound

This paper cites Random forests.Machine learning, 45:5–32, 2001.

MOSS: Multi-Objective Optimization for Stable Rule Sets Random forests.Machine learning, 45:5–32, 2001

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T11:53:56.173909Z

Source-reported events for the cited work

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Observation cd7c1729-13ab-4569-af60-820f7a4d1941 · outbound

This paper cites API design for machine learning software: experiences from the scikit-learn project.

MOSS: Multi-Objective Optimization for Stable Rule Sets API design for machine learning software: experiences from the scikit-learn project

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:04.314881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b105a66d-f628-4bd7-9684-449e90c32307 · outbound

This paper cites Efficient exploration of the rashomon set of rule-set models.

MOSS: Multi-Objective Optimization for Stable Rule Sets Efficient exploration of the rashomon set of rule-set models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:04.056686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9519d9ee-6d91-4da9-ad6d-3f53557faaf8 · outbound

This paper cites An outer-approximation algorithm for a class of mixed-integer nonlinear programs.Mathematical programming, 36: 307–339, 1986.

MOSS: Multi-Objective Optimization for Stable Rule Sets An outer-approximation algorithm for a class of mixed-integer nonlinear programs.Mathematical programming, 36: 307–339, 1986

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:03.818716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bb32470b-36d4-4f66-bad6-c6d8986a1f0d · outbound

This paper cites A tutorial on multiobjective op- timization: fundamentals and evolutionary methods.Natural computing, 17: 585–609, 2018.

MOSS: Multi-Objective Optimization for Stable Rule Sets A tutorial on multiobjective op- timization: fundamentals and evolutionary methods.Natural computing, 17: 585–609, 2018

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:03.596943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d5a35721-aab4-42f0-8ae9-ef69d5fc6c74 · outbound

This paper cites The low response score (lrs) a metric to locate, predict, and manage hard-to-survey populations.Public Opinion Quarterly, 81 (1):144–156, 2017.

MOSS: Multi-Objective Optimization for Stable Rule Sets The low response score (lrs) a metric to locate, predict, and manage hard-to-survey populations.Public Opinion Quarterly, 81 (1):144–156, 2017

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:03.297789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b0d63729-2b14-4d49-96fb-4a8cc7221337 · outbound

This paper cites Solving mixed integer nonlinear programs by outer approximation.Mathematical programming, 66:327–349, 1994.

MOSS: Multi-Objective Optimization for Stable Rule Sets Solving mixed integer nonlinear programs by outer approximation.Mathematical programming, 66:327–349, 1994

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:03.108035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4c9e2590-8851-4274-a7ba-aed92581eeaa · outbound

This paper cites Predictive learning via rule ensembles.

MOSS: Multi-Objective Optimization for Stable Rule Sets Predictive learning via rule ensembles

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T11:53:57.026913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ab732a7-c223-414c-bf30-919882005204 · outbound

This paper cites Seabird trophic position across three ocean regions tracks ecosystem differences.Frontiers in Marine Science, 5:317, 2018.

MOSS: Multi-Objective Optimization for Stable Rule Sets Seabird trophic position across three ocean regions tracks ecosystem differences.Frontiers in Marine Science, 5:317, 2018

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:02.877598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b8b77e71-82a6-47a8-8e44-16cc58214123 · outbound

This paper cites Gurobi Optimizer Reference Manual, 2024.

MOSS: Multi-Objective Optimization for Stable Rule Sets Gurobi Optimizer Reference Manual, 2024

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T11:53:57.241180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b072cb49-f9bf-4d84-9036-eda798f10698 · outbound

This paper cites an unresolved cited work.

MOSS: Multi-Objective Optimization for Stable Rule Sets Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:54:02.674173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b043e9c4-1b07-471a-ab53-4b977721374e · outbound

This paper cites An introduction to glmnet.

MOSS: Multi-Objective Optimization for Stable Rule Sets An introduction to glmnet

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:02.430721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0a30adbb-c338-4ff2-9e11-f69758b40b61 · outbound

This paper cites L0learn: A scalable package for sparse learning using l0 regularization.Journal of Machine Learning Research, 24(205):1–8, 2023.

MOSS: Multi-Objective Optimization for Stable Rule Sets L0learn: A scalable package for sparse learning using l0 regularization.Journal of Machine Learning Research, 24(205):1–8, 2023

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:02.217017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 217f4385-b7af-4f75-8e56-ee39404e60fe · outbound

This paper cites The 2020 census & the environment: How census data are used for environmental justice & climate action.

MOSS: Multi-Objective Optimization for Stable Rule Sets The 2020 census & the environment: How census data are used for environmental justice & climate action

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:02.007417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 625928c2-d42b-41fd-bc47-e2ffe7584632 · outbound

This paper cites Fire: An optimization approach for fast inter- pretable rule extraction.

MOSS: Multi-Objective Optimization for Stable Rule Sets Fire: An optimization approach for fast inter- pretable rule extraction

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:01.485011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f737874e-c2f3-41f3-833c-5f388ad910a4 · outbound

This paper cites an unresolved cited work.

MOSS: Multi-Objective Optimization for Stable Rule Sets Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:54:01.735556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7af3f63f-ba8b-4c44-8b28-1feebfc5b687 · outbound

This paper cites Subset selection with shrinkage: Sparse linear modeling when the snr is low.Operations Research, 71 (1):129–147, 2023.

MOSS: Multi-Objective Optimization for Stable Rule Sets Subset selection with shrinkage: Sparse linear modeling when the snr is low.Operations Research, 71 (1):129–147, 2023

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:01.260900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 23c968ae-7909-416a-9bb5-2a452e63e030 · outbound

This paper cites Computing the Collection of Good Models for Rule Lists.

MOSS: Multi-Objective Optimization for Stable Rule Sets Computing the Collection of Good Models for Rule Lists

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T11:53:57.934582Z

Source-reported events for the cited work

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Observation 5c3f265b-467c-4ebc-9a53-f529cb30ba9b · outbound

This paper cites Definitions, methods, and applications in interpretable machine learning.

MOSS: Multi-Objective Optimization for Stable Rule Sets Definitions, methods, and applications in interpretable machine learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:01.049961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d0fcac56-9902-4c43-9b45-8e66dd8521fa · outbound

This paper cites Stability selection.Journal of the Royal Statistical Society Series B: Statistical Methodology, 72(4):417–473, 2010.

MOSS: Multi-Objective Optimization for Stable Rule Sets Stability selection.Journal of the Royal Statistical Society Series B: Statistical Methodology, 72(4):417–473, 2010

Reference 26

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Source-reported events for the cited work

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Observation 85283e7e-7ab9-444b-920f-c809860f1159 · outbound

This paper cites Routledge, 2005.

MOSS: Multi-Objective Optimization for Stable Rule Sets Routledge, 2005

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T11:53:58.260355Z

Source-reported events for the cited work

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Observation f92a5a29-3263-4e66-a61c-272be630b214 · outbound

This paper cites On the stability of feature selection algorithms.Journal of Machine Learning Research, 18(174):1–54, 2018.

MOSS: Multi-Objective Optimization for Stable Rule Sets On the stability of feature selection algorithms.Journal of Machine Learning Research, 18(174):1–54, 2018

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:00.801094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 34bf1a51-2e50-4500-a9e3-c14aaa1d926f · outbound

This paper cites Census Bureau.

MOSS: Multi-Objective Optimization for Stable Rule Sets Census Bureau

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:00.324362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6313e6f1-5c27-4386-8ee1-825919d9068d · outbound

This paper cites Algorithms for interpretable machine learning.

MOSS: Multi-Objective Optimization for Stable Rule Sets Algorithms for interpretable machine learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:00.562877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 166f3565-5244-40fb-8460-827c0ed8bac9 · outbound

This paper cites Generalized linear rule models.

MOSS: Multi-Objective Optimization for Stable Rule Sets Generalized linear rule models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:54:00.149142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0ce9779b-7a5b-41a1-ad10-0e8afc94071e · outbound

This paper cites van Rijn, Bernd Bischl, and Luis Torgo.

MOSS: Multi-Objective Optimization for Stable Rule Sets van Rijn, Bernd Bischl, and Luis Torgo

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T11:53:58.474949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd9bb8b9-9d27-4434-9f4c-86ce0f04f211 · outbound

This paper cites Stability.

MOSS: Multi-Objective Optimization for Stable Rule Sets Stability

Reference 33

Resolution: parse uncertain; raw_fallback, observed 2026-08-07T11:53:59.705557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 45925792-61ef-4cd9-9ac3-32be1d5f2648 · outbound

This paper cites Exploring the whole rashomon set of sparse decision trees.Advances in neural information processing systems, 35:14071–14084, 2022.

MOSS: Multi-Objective Optimization for Stable Rule Sets Exploring the whole rashomon set of sparse decision trees.Advances in neural information processing systems, 35:14071–14084, 2022

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:59.932147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation de830013-21d1-45ca-9e58-83b614a1a1ca · outbound

This paper cites Veridical data science.

MOSS: Multi-Objective Optimization for Stable Rule Sets Veridical data science

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:59.304019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d4fe08ae-c630-4aa8-98cb-8e9fc144670e · outbound

This paper cites Three principles of data science: predictability, computability, and stability (pcs).

MOSS: Multi-Objective Optimization for Stable Rule Sets Three principles of data science: predictability, computability, and stability (pcs)

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:59.540734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4a6372c3-ab54-45bc-91ee-bdf6705cd73c · outbound

This paper cites We take the scenario with the lower objective value as the solution for Problem 3.

MOSS: Multi-Objective Optimization for Stable Rule Sets We take the scenario with the lower objective value as the solution for Problem 3

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:59.123470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3fee0025-098d-460b-85dc-b734f7260800 · outbound

This paper cites an unresolved cited work.

MOSS: Multi-Objective Optimization for Stable Rule Sets Unresolved cited work

Reference 2019

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:54:05.183041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.