Paper Citation Record · LEDGER

Symbolic Regression is NP-hard

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2207.01018.

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

pith.paper-citation-record.v1
2207.01018 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 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 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:02:19.727891Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T20:17:21.414554Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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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 8942bdfe-eec4-4bd5-858d-2f9a5f036600 · inbound

Neuro-Symbolic AI for Analytical Solutions of Differential Equations cites this paper.

Neuro-Symbolic AI for Analytical Solutions of Differential Equations Symbolic Regression is NP-hard

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:35:21.181138Z

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 c92fa8d9-8026-49ab-b8d0-8d5e5e60e30b · inbound

SyMANTIC: An Efficient Symbolic Regression Method for Interpretable and Parsimonious Model Discovery in Science and Beyond cites this paper.

SyMANTIC: An Efficient Symbolic Regression Method for Interpretable and Parsimonious Model Discovery in Science and Beyond Symbolic Regression is NP-hard

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T05:02:19.727891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8efbb68e-b402-4ad2-b752-db3ea2f82d5e · inbound

Modeling the Optical Properties of Biological Structures using Symbolic Regression cites this paper.

Modeling the Optical Properties of Biological Structures using Symbolic Regression Symbolic Regression is NP-hard

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T11:35:35.264685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e67867d1-d2b5-4f93-ba38-ca30b2bc601a · inbound

SymMatika: Structure-Aware Symbolic Discovery cites this paper.

SymMatika: Structure-Aware Symbolic Discovery Symbolic Regression is NP-hard

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:38.380681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08d539f8-f912-458f-87fc-d8648a474e8a · inbound

$\mathcal{CP}$-Analyses with Symbolic Regression cites this paper.

$\mathcal{CP}$-Analyses with Symbolic Regression Symbolic Regression is NP-hard

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:34.545770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf6ac84e-6953-4c0e-88db-7ebf586aa211 · inbound

Advancing network resilience theories with symbolized reinforcement learning cites this paper.

Advancing network resilience theories with symbolized reinforcement learning Symbolic Regression is NP-hard

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T20:10:44.331834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3a67289-215a-4c18-a192-d0696aa68806 · inbound

Fast Symbolic Regression Benchmarking cites this paper.

Fast Symbolic Regression Benchmarking Symbolic Regression is NP-hard

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T18:37:58.157921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50c42e7e-1ad8-4ac5-ad7a-735363934165 · inbound

Symbolic Regression for Shared Expressions: Introducing Partial Parameter Sharing cites this paper.

Symbolic Regression for Shared Expressions: Introducing Partial Parameter Sharing Symbolic Regression is NP-hard

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T12:11:28.133414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc8444cc-5d28-4f01-a663-43990cdf9d7b · inbound

ECSEL: Explainable Classification via Signomial Equation Learning cites this paper.

ECSEL: Explainable Classification via Signomial Equation Learning Symbolic Regression is NP-hard

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T06:52:30.676608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35ca5f68-6a71-43ba-8bbd-63a5e7883f9c · inbound

LLM-Based Scientific Equation Discovery via Physics-Informed Token-Regularized Policy Optimization cites this paper.

LLM-Based Scientific Equation Discovery via Physics-Informed Token-Regularized Policy Optimization Symbolic Regression is NP-hard

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-03T01:09:56.014837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19d25c30-c1f2-4ef5-a152-3f6eaa82c8ba · inbound

Discovery of Nonlinear Dynamics with Automated Basis Function Generation cites this paper.

Discovery of Nonlinear Dynamics with Automated Basis Function Generation Symbolic Regression is NP-hard

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:21:25.803359Z

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 d29d3a15-edf7-4f6b-a758-f3af7e471bcb · inbound

The finite expression method for turbulent dynamics with high-order moment recovery cites this paper.

The finite expression method for turbulent dynamics with high-order moment recovery Symbolic Regression is NP-hard

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:41:23.482353Z

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 48f7ad16-cbea-4082-8195-e2eea3b8d78d · inbound

Learning dynamical systems with biochemically informed neural ordinary differential equations cites this paper.

Learning dynamical systems with biochemically informed neural ordinary differential equations Symbolic Regression is NP-hard

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:34:45.696206Z

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 6cb5a4b3-8f15-47cf-88f2-5cfa4a2bef8b · inbound

FunctionEvolve: Structure-Guided Symbolic Regression with LLMs cites this paper.

FunctionEvolve: Structure-Guided Symbolic Regression with LLMs Symbolic Regression is NP-hard

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:17:09.472924Z

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 aab64f7c-6a11-4838-963a-b86fa3c4b2a0 · inbound

CMBolic: Symbolic emulators for the Cosmic Microwave Background. I. Lensing cites this paper.

CMBolic: Symbolic emulators for the Cosmic Microwave Background. I. Lensing Symbolic Regression is NP-hard

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-07-02T20:17:21.416128Z

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 9600e81f-225e-470f-a0eb-73bd2f8fa21b · inbound

MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models cites this paper.

MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models Symbolic Regression is NP-hard

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-03T04:39:28.636852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.