Paper Citation Record · LEDGER

A Data-Free Symbolic Regression Approach for Solving Equations

As of 17 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2606.07152.

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

pith.paper-citation-record.v1
2606.07152 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T20:24:57.810972Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

23 of 23 outbound references displayed

verified exact3
verified fuzzy0
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6d8caadd-527d-48da-9163-b91ae2ef1eb9 · outbound

This paper cites Neural symbolic regression that scales.

A Data-Free Symbolic Regression Approach for Solving Equations Neural symbolic regression that scales

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f16c91df-711f-4b33-847e-8ab98e7ca590 · outbound

This paper cites Discovering governing equations from data by sparse identification of nonlinear dynamical systems.Proceedings of the national academy of sciences, 113(15):3932–3937, 2016.

A Data-Free Symbolic Regression Approach for Solving Equations Discovering governing equations from data by sparse identification of nonlinear dynamical systems.Proceedings of the national academy of sciences, 113(15):3932–3937, 2016

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca80ab44-45fc-41a2-b307-afa02ed0cf59 · outbound

This paper cites Operon c++ an efficient genetic programming framework for symbolic regression.

A Data-Free Symbolic Regression Approach for Solving Equations Operon c++ an efficient genetic programming framework for symbolic regression

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa89b598-0ad9-4ed0-89b2-a2e595a4f7f4 · outbound

This paper cites Undergraduate Texts in Mathematics, p.

A Data-Free Symbolic Regression Approach for Solving Equations Undergraduate Texts in Mathematics, p

Reference 4

Resolution: metadata mismatch; doi, observed 2026-06-27T20:31:14.358841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 68369d2b-6db2-4873-8844-eab670c61d93 · outbound

This paper cites Complex equation learner: Rational symbolic regression with gradient descent in complex domain, 2026.

A Data-Free Symbolic Regression Approach for Solving Equations Complex equation learner: Rational symbolic regression with gradient descent in complex domain, 2026

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6305562f-92b4-4de0-af0c-f5709e65cb09 · outbound

This paper cites End-to- end symbolic regression with transformers.Advances in Neural Information Processing Systems, 35: 10269–10281, 2022.

A Data-Free Symbolic Regression Approach for Solving Equations End-to- end symbolic regression with transformers.Advances in Neural Information Processing Systems, 35: 10269–10281, 2022

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c81e3db-49f0-4357-a524-d3481fb05b5b · outbound

This paper cites Adam: A Method for Stochastic Optimization.

A Data-Free Symbolic Regression Approach for Solving Equations Adam: A Method for Stochastic Optimization

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-07-02T20:27:22.454302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8bac036b-444d-4eb8-b4bc-cc6c341f5663 · outbound

This paper cites An algorithm for solving second order linear homogeneous differential equations.

A Data-Free Symbolic Regression Approach for Solving Equations An algorithm for solving second order linear homogeneous differential equations

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88c044c9-c816-4501-bdf8-2155da3bdfc6 · outbound

This paper cites Genetic programming as a means for programming computers by natural selection.

A Data-Free Symbolic Regression Approach for Solving Equations Genetic programming as a means for programming computers by natural selection

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc00ca38-c58c-4c7c-8c06-297d6cd62194 · outbound

This paper cites Artificial neural networks for solving ordinary and partial differential equations.IEEE transactions on neural networks, 9(5):987–1000, 1998.

A Data-Free Symbolic Regression Approach for Solving Equations Artificial neural networks for solving ordinary and partial differential equations.IEEE transactions on neural networks, 9(5):987–1000, 1998

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a880659-96e5-4af0-adf0-2483a49312db · outbound

This paper cites Hou, and Max Tegmark.

A Data-Free Symbolic Regression Approach for Solving Equations Hou, and Max Tegmark

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 798174b3-e343-4691-b4fc-aaaec85d1b39 · outbound

This paper cites Interpretable scientific discovery with symbolic regression: a review.Artificial Intelligence Review, 57(1):2, 2024.

A Data-Free Symbolic Regression Approach for Solving Equations Interpretable scientific discovery with symbolic regression: a review.Artificial Intelligence Review, 57(1):2, 2024

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5feed48-f12b-45da-b48a-d8aa633844eb · outbound

This paper cites Extrapolation and learning equations.

A Data-Free Symbolic Regression Approach for Solving Equations Extrapolation and learning equations

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-07-02T20:27:22.448508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3fedd43e-9699-4fd1-955d-f8c927460cb0 · outbound

This paper cites Mundhenk, Claudio Prata Santiago, Soo Kyung Kim, and Joanne Taery Kim.

A Data-Free Symbolic Regression Approach for Solving Equations Mundhenk, Claudio Prata Santiago, Soo Kyung Kim, and Joanne Taery Kim

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d81204c5-9e52-4721-b959-c26a759cab40 · outbound

This paper cites an unresolved cited work.

A Data-Free Symbolic Regression Approach for Solving Equations Unresolved cited work

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a8360a3-085d-4737-92f6-42f2935c2c48 · outbound

This paper cites Learning equations for extrapolation and control.

A Data-Free Symbolic Regression Approach for Solving Equations Learning equations for extrapolation and control

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf8bc48b-31d6-4d0b-a215-9c4faa1da73e · outbound

This paper cites Dgm: A deep learning algorithm for solving partial differential equations.Journal of computational physics, 375:1339–1364, 2018.

A Data-Free Symbolic Regression Approach for Solving Equations Dgm: A deep learning algorithm for solving partial differential equations.Journal of computational physics, 375:1339–1364, 2018

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8d231e7-4c63-4012-9a88-8c75f1f9385b · outbound

This paper cites Interac- tive symbolic regression with co-design mechanism through offline reinforcement learning.Nature Communications, 16(1):3930, 2025.

A Data-Free Symbolic Regression Approach for Solving Equations Interac- tive symbolic regression with co-design mechanism through offline reinforcement learning.Nature Communications, 16(1):3930, 2025

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a332c013-6278-4636-a9c4-c946aa1adbf2 · outbound

This paper cites Review of pysr: high-performance symbolic regression in python and julia, 2025.

A Data-Free Symbolic Regression Approach for Solving Equations Review of pysr: high-performance symbolic regression in python and julia, 2025

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40e6e7f2-d76a-4535-bcfd-2973c099a0e0 · outbound

This paper cites Cambridge university press, 2003.

A Data-Free Symbolic Regression Approach for Solving Equations Cambridge university press, 2003

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32102ea2-a3df-4301-afdb-8a0bb0cdeb2c · outbound

This paper cites Informed Equation Learning.

A Data-Free Symbolic Regression Approach for Solving Equations Informed Equation Learning

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-02T20:27:22.451513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8830b3dd-716f-442b-b68e-c468d1a2c681 · outbound

This paper cites Symbolic computation in algebra, geometry, and differential equations.Information and Computation, 301:105200, 2024.

A Data-Free Symbolic Regression Approach for Solving Equations Symbolic computation in algebra, geometry, and differential equations.Information and Computation, 301:105200, 2024

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb1f5d42-a9cc-444e-8667-bfa7179c6e41 · outbound

This paper cites The deep ritz method: a deep learning-based numerical algorithm for solving varia- tional problems.Communications in Mathematics and Statistics, 6(1):1–12, 2018.

A Data-Free Symbolic Regression Approach for Solving Equations The deep ritz method: a deep learning-based numerical algorithm for solving varia- tional problems.Communications in Mathematics and Statistics, 6(1):1–12, 2018

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-27T20:24:57.810972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.