Paper Citation Record · LEDGER

(Exhaustive) Symbolic Regression and model selection by minimum description length

As of 8 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 4 inbound Pith citation observations for arXiv:2507.13033.

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

pith.paper-citation-record.v1
2507.13033 v1

Coverage vector

measured 37 of 37 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-06T16:41:09.907897Z

measured 41 of 41 standing notices

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measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T20:08:33.861358Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T12:15:01.137692Z

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

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Outbound references

Observation 046891bc-cad5-4a91-9f0d-d10434c3017d · outbound

This paper cites syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy.

(Exhaustive) Symbolic Regression and model selection by minimum description length syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy

Reference 1

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Observation df3fb50a-34d8-41e8-a8bc-9851894106c2 · outbound

This paper cites 1950 I.—COMPUTING MACHINERY AND INTELLIGENCE.MindLIX, 433–460.

(Exhaustive) Symbolic Regression and model selection by minimum description length 1950 I.—COMPUTING MACHINERY AND INTELLIGENCE.MindLIX, 433–460

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T16:41:05.535288Z

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Observation 43ba99ae-3c07-441d-a992-856bea68bf0b · outbound

This paper cites 1989Genetic Algorithms in Search, Optimization and Machine Learning.

(Exhaustive) Symbolic Regression and model selection by minimum description length 1989Genetic Algorithms in Search, Optimization and Machine Learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:41:12.071242Z

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Observation f9a72290-ff58-45f9-8c84-5e15feac490d · outbound

This paper cites 2004Practical genetic algorithms.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2004Practical genetic algorithms

Reference 4

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Observation ce14191f-2ca1-451f-9e7c-bde7e1a1bf16 · outbound

This paper cites 2020 Operon C++: an efficient genetic programming framework for symbolic regression.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2020 Operon C++: an efficient genetic programming framework for symbolic regression

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T16:41:05.755536Z

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Observation 50df5115-b6e8-4c51-9a14-178b3cf30de4 · outbound

This paper cites 2020 Discovering Symbolic Models from Deep Learning with Inductive Biases.NeurIPS 2020.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2020 Discovering Symbolic Models from Deep Learning with Inductive Biases.NeurIPS 2020

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:41:11.735199Z

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Observation a3cdcab6-cfc2-4d67-8d0f-2a5e3f2aa709 · outbound

This paper cites Data Modeler 9.5.1.

(Exhaustive) Symbolic Regression and model selection by minimum description length Data Modeler 9.5.1

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:41:11.569557Z

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Observation b2e6c5ef-1923-46ad-802d-9122c67d8b9f · outbound

This paper cites 2009 Order of Nonlinearity as a Complexity Measure for Models Generated by Symbolic Regression via Pareto Genetic Programming.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2009 Order of Nonlinearity as a Complexity Measure for Models Generated by Symbolic Regression via Pareto Genetic Programming

Reference 8

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Observation 22934dfa-0d04-402e-b257-37ec7ed96165 · outbound

This paper cites 2024 Exhaustive Symbolic Regression.IEEE Transactions on Evolutionary Computation28, 950–964.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2024 Exhaustive Symbolic Regression.IEEE Transactions on Evolutionary Computation28, 950–964

Reference 9

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Observation 032664ea-9542-4179-9646-f5581c87bb9d · outbound

This paper cites 2022 Exhaustive Symbolic Regression Function Sets.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2022 Exhaustive Symbolic Regression Function Sets

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T16:41:06.162129Z

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Observation 6d2926cb-b3a3-4b86-9cdd-1843e3f59e9a · outbound

This paper cites 1996 The Structure of Cold Dark Matter Halos.ApJ462,.

(Exhaustive) Symbolic Regression and model selection by minimum description length 1996 The Structure of Cold Dark Matter Halos.ApJ462,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:41:11.406530Z

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Observation 05ccaf6b-e6ae-47aa-85d0-da1b3692cd02 · outbound

This paper cites Contemporary Symbolic Regression Methods and their Relative Performance.

(Exhaustive) Symbolic Regression and model selection by minimum description length Contemporary Symbolic Regression Methods and their Relative Performance

Reference 12

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Observation a32cb2c0-604a-47ef-9154-fd4b3d81f41a · outbound

This paper cites an unresolved cited work.

(Exhaustive) Symbolic Regression and model selection by minimum description length Unresolved cited work

Reference 13

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Observation 9f941d9c-82a2-44a4-8fe5-d0afdcc31bd9 · outbound

This paper cites An Approach to Symbolic Regression Using Feyn.

(Exhaustive) Symbolic Regression and model selection by minimum description length An Approach to Symbolic Regression Using Feyn

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T16:41:06.601222Z

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Observation 07e60e68-6f3c-4eae-8416-9bf6beea35ec · outbound

This paper cites 2020 PySR: Fast & Parallelized Symbolic Regression in Python/Julia.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2020 PySR: Fast & Parallelized Symbolic Regression in Python/Julia

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T16:41:06.686197Z

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Observation 556759cd-d133-4cf4-be4a-431ac035cc9a · outbound

This paper cites 1978 Modeling by shortest data description.Automatica14, 465–471.

(Exhaustive) Symbolic Regression and model selection by minimum description length 1978 Modeling by shortest data description.Automatica14, 465–471

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T16:41:06.809691Z

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Observation 673bb6e8-4901-4ad6-907c-1bacafcc3b18 · outbound

This paper cites Minimum Description Length Revisited.

(Exhaustive) Symbolic Regression and model selection by minimum description length Minimum Description Length Revisited

Reference 17

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Observation 7ba3db17-33ef-4b1d-914f-2815303aa888 · outbound

This paper cites 1991Elements of Information Theory.

(Exhaustive) Symbolic Regression and model selection by minimum description length 1991Elements of Information Theory

Reference 18

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Observation 4d7f5a7b-dd7f-4a00-abdc-6eaf9d4a7422 · outbound

This paper cites Priors for symbolic regression.

(Exhaustive) Symbolic Regression and model selection by minimum description length Priors for symbolic regression

Reference 19

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Observation 4ad03b97-cf72-43a6-a8cd-84abd018ae2a · outbound

This paper cites 1987 Estimation of probabilities from sparse data for the language model component of a speech recognizer.IEEE Trans.

(Exhaustive) Symbolic Regression and model selection by minimum description length 1987 Estimation of probabilities from sparse data for the language model component of a speech recognizer.IEEE Trans

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:41:11.084419Z

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Observation f8211a84-3bb8-460f-a2b7-3f618b913503 · outbound

This paper cites 2022 Unveiling the Universe with emerging cosmological probes.Living Reviews in Relativity25, 6.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2022 Unveiling the Universe with emerging cosmological probes.Living Reviews in Relativity25, 6

Reference 21

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Observation 5c930d52-a835-4227-a814-5be203f9e7a3 · outbound

This paper cites The Pantheon+ Analysis: The Full Dataset and Light-Curve Release.

(Exhaustive) Symbolic Regression and model selection by minimum description length The Pantheon+ Analysis: The Full Dataset and Light-Curve Release

Reference 22

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Observation b289bdc4-35fc-4d74-b6ca-46fddfd4c22d · outbound

This paper cites 2023 On the functional form of the radial acceleration relation.MNRAS521, 1817–1831.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2023 On the functional form of the radial acceleration relation.MNRAS521, 1817–1831

Reference 23

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Observation 414412f7-7c3a-4eba-b4b3-3b55120d2a5c · outbound

This paper cites 1983a A modification of the Newtonian dynamics as a possible alternative to the hidden mass hypothesis.ApJ270, 365–370.

(Exhaustive) Symbolic Regression and model selection by minimum description length 1983a A modification of the Newtonian dynamics as a possible alternative to the hidden mass hypothesis.ApJ270, 365–370

Reference 24

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Observation 315d0001-00b2-4812-9eed-51158874e3ac · outbound

This paper cites 1983b A Modification of the Newtonian Dynamics - Implications for Galaxy Systems.ApJ270, 384.

(Exhaustive) Symbolic Regression and model selection by minimum description length 1983b A Modification of the Newtonian Dynamics - Implications for Galaxy Systems.ApJ270, 384

Reference 25

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Observation 1616e196-c4f7-429c-a8b6-25a7c94439e4 · outbound

This paper cites 1983c A modification of the Newtonian dynamics - Implications for galaxies.ApJ 270, 371–389.

(Exhaustive) Symbolic Regression and model selection by minimum description length 1983c A modification of the Newtonian dynamics - Implications for galaxies.ApJ 270, 371–389

Reference 26

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Observation cce5990f-fa10-45b4-8833-da7e3338399a · outbound

This paper cites Modified Newtonian Dynamics: Observational Successes and Failures.

(Exhaustive) Symbolic Regression and model selection by minimum description length Modified Newtonian Dynamics: Observational Successes and Failures

Reference 27

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Observation 678bdbe6-6e96-45de-a66d-62a053f6a07b · outbound

This paper cites 2017 One Law to Rule Them All: The Radial Acceleration Relation of Galaxies.ApJ836, 152.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2017 One Law to Rule Them All: The Radial Acceleration Relation of Galaxies.ApJ836, 152

Reference 28

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Observation 2f5f707f-f3c2-491f-ae15-1ff7d523840f · outbound

This paper cites 2023 The underlying radial acceleration relation.MNRAS526, 3342–3351.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2023 The underlying radial acceleration relation.MNRAS526, 3342–3351

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T16:41:08.638268Z

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Observation 5b87fd6b-81f9-433f-bf29-58f50110417e · outbound

This paper cites 2023 On the fundamentality of the radial acceleration relation for late-type galaxy dynamics.MNRAS525, 6130–6145.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2023 On the fundamentality of the radial acceleration relation for late-type galaxy dynamics.MNRAS525, 6130–6145

Reference 30

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This paper cites 2024 Radial acceleration relation of galaxies with joint kinematic and weak-lensing data.JCAP2024, 020.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2024 Radial acceleration relation of galaxies with joint kinematic and weak-lensing data.JCAP2024, 020

Reference 31

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This paper cites 2024 Optimal inflationary potentials.PRD109, 083524.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2024 Optimal inflationary potentials.PRD109, 083524

Reference 32

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Observation 50eb6f3c-79ae-44f6-b1e2-d47bc9ffe4b1 · outbound

This paper cites Encyclopaedia Inflationaris.

(Exhaustive) Symbolic Regression and model selection by minimum description length Encyclopaedia Inflationaris

Reference 33

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Observation a149e527-4c7f-4443-ba99-cdb1f0122496 · outbound

This paper cites 2020 Planck 2018 results.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2020 Planck 2018 results

Reference 34

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This paper cites 2023 Updated constraints on amplitude and tilt of the tensor primordial spectrum.JCAP2023, 062.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2023 Updated constraints on amplitude and tilt of the tensor primordial spectrum.JCAP2023, 062

Reference 35

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Observation 4e915f29-6fea-4678-89b6-22f2f118ab8f · outbound

This paper cites 2023 GECCO’2022 Symbolic Regression Competition: Post-Analysis of the Operon Framework.

(Exhaustive) Symbolic Regression and model selection by minimum description length 2023 GECCO’2022 Symbolic Regression Competition: Post-Analysis of the Operon Framework

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T16:41:09.777457Z

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Observation a73f6ebc-30e5-44a0-af06-ab12d2f7825b · outbound

This paper cites 1976 An analytic expression for the luminosity function for galaxies..ApJ203, 297–306.

(Exhaustive) Symbolic Regression and model selection by minimum description length 1976 An analytic expression for the luminosity function for galaxies..ApJ203, 297–306

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T16:41:09.907897Z

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Pith citing papers

Observation 86bc845c-d0a0-4d31-9e5d-1f619a0feba2 · inbound

Comparison of symbolic regression algorithms in Star/galaxy/quasar separation cites this paper.

Comparison of symbolic regression algorithms in Star/galaxy/quasar separation (Exhaustive) Symbolic Regression and model selection by minimum description length

Reference 10

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Observation 849de635-669e-4428-9bf9-1ae30d86cb7a · inbound

Model-independent constraints on generalized FLRW consistency relations with bootstrap-based symbolic regression cites this paper.

Model-independent constraints on generalized FLRW consistency relations with bootstrap-based symbolic regression (Exhaustive) Symbolic Regression and model selection by minimum description length

Reference 25

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Observation c1f9ab9f-517b-4951-bd1c-4bf6f932a17e · inbound

The functional form of galaxy and halo luminosity and mass functions cites this paper.

The functional form of galaxy and halo luminosity and mass functions (Exhaustive) Symbolic Regression and model selection by minimum description length

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-08T22:54:24.646384Z

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Observation 1973bbb0-f903-4c8b-8f10-ad9b0b5edf70 · inbound

Data-Driven Discovery of a Simple Phantom-Crossing Dark Energy Parametrization cites this paper.

Data-Driven Discovery of a Simple Phantom-Crossing Dark Energy Parametrization (Exhaustive) Symbolic Regression and model selection by minimum description length

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-03T22:08:59.559231Z

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