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Paper Citation Record · LEDGER

Contemporary Symbolic Regression Methods and their Relative Performance

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2107.14351.

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

pith.paper-citation-record.v1
2107.14351 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 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 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:15:18.987743Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T02:37:34.637254Z

Reference resolution

0 of 0 outbound references displayed

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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 a94de04e-2f10-49c1-a792-4af181a83b0f · inbound

Bridging the Domain Gap in Equation Distillation with Reinforcement Feedback cites this paper.

Bridging the Domain Gap in Equation Distillation with Reinforcement Feedback Contemporary Symbolic Regression Methods and their Relative Performance

Reference 8

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unresolved
no resolver link, observed 2026-08-07T15:19:38.598819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:19:38.598819Z digest=sha256:7e8384c5d462790cd7535c786a957c336d8feae315909335c9019d33e82b0741

Observation 24a08719-8017-44c8-9391-92a9b1453b5b · inbound

Diffusion-Based Symbolic Regression cites this paper.

Diffusion-Based Symbolic Regression Contemporary Symbolic Regression Methods and their Relative Performance

Reference 13

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unresolved
no resolver link, observed 2026-08-07T12:35:36.742558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:36.742558Z digest=sha256:ba421fe29dcac34bea4a3f0f89be86fa8415b77e53dd096a366a4a6cf3439d81

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

(Exhaustive) Symbolic Regression and model selection by minimum description length cites this paper.

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

Reference 12

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unresolved
no resolver link, observed 2026-08-06T16:41:06.378542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 36bd77cb-c8db-4e7f-b07a-81fea35a342c · inbound

Fast Symbolic Regression Benchmarking cites this paper.

Fast Symbolic Regression Benchmarking Contemporary Symbolic Regression Methods and their Relative Performance

Reference 2

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unresolved
no resolver link, observed 2026-08-05T18:37:57.349266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:37:57.349266Z digest=sha256:e72c4e2f79cd8706c8287dda0a3c61d8e52ab34cec1831adae295444bbadaeb9

Observation fd57189e-5b38-4d44-8463-827cb3701542 · inbound

Exploring Multi-view Symbolic Regression methods in physical sciences cites this paper.

Exploring Multi-view Symbolic Regression methods in physical sciences Contemporary Symbolic Regression Methods and their Relative Performance

Reference 17

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unresolved
no resolver link, observed 2026-08-05T12:35:34.918092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:35:34.918092Z digest=sha256:3b9c8dcdef3fb5f5f8f45487d39d10349c5472d4bbc48d79842af65c89910b6a

Observation 16841cff-9f5b-423c-a51f-290a3fd72049 · inbound

In-Context Symbolic Regression for Robustness-Improved Kolmogorov-Arnold Networks cites this paper.

In-Context Symbolic Regression for Robustness-Improved Kolmogorov-Arnold Networks Contemporary Symbolic Regression Methods and their Relative Performance

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T10:15:26.746699Z

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.

source=pdf_text observed=2026-05-15T10:13:26.496670Z digest=sha256:d00849b0eb64acad1d33a0086de6dcb8f08c0d2a9452b1d355f406213388665d

Observation e1be0c5d-e5f9-4da5-bfc1-1a18d516c932 · inbound

Programmatic Context Augmentation for LLM-based Symbolic Regression cites this paper.

Programmatic Context Augmentation for LLM-based Symbolic Regression Contemporary Symbolic Regression Methods and their Relative Performance

Reference 31

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metadata mismatch
arxiv_id, observed 2026-05-09T06:25:48.473754Z

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.

source=arxiv_source observed=2026-05-08T18:26:09.810673Z digest=sha256:7e971fae7edc9020d728c0208802a64fbdd5808cd66bc936eacbdbd2cb4f095c

Observation c8d3d54c-ff74-4138-8244-72e10654267f · inbound

Symbolic Classification-Enabled LHC Limits Online BSM Global Fits cites this paper.

Symbolic Classification-Enabled LHC Limits Online BSM Global Fits Contemporary Symbolic Regression Methods and their Relative Performance

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-22T05:04:37.101463Z

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.

source=pdf_text observed=2026-05-22T05:03:33.071351Z digest=sha256:fac26f42206ce427dc6fca2e6c0ba7ac9c1be96cb7cf8fa436246c0b4622eb49

Observation 9bb3abf6-9375-41a9-b0ae-e3e6c0d8f21b · inbound

GP-GOMEA with GPU-Based Fitness Evaluations: Design and Performance Analysis cites this paper.

GP-GOMEA with GPU-Based Fitness Evaluations: Design and Performance Analysis Contemporary Symbolic Regression Methods and their Relative Performance

Reference 4

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verified exact
arxiv_id, observed 2026-06-28T20:22:37.111515Z

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.

source=pdf_text observed=2026-06-28T20:21:31.456568Z digest=sha256:9867b50d3261eaf4951e4ca688df7d7135d48eeaa4aa12273fdc757c9f160dc5

Observation e15e3e86-4784-4594-96ae-4781c2c21084 · inbound

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

FunctionEvolve: Structure-Guided Symbolic Regression with LLMs Contemporary Symbolic Regression Methods and their Relative Performance

Reference 37

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verified exact
arxiv_id, observed 2026-07-02T16:17:09.468394Z

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.

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Observation b524a645-ba45-4a23-bd07-4bcea6c65f8e · inbound

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

CMBolic: Symbolic emulators for the Cosmic Microwave Background. I. Lensing Contemporary Symbolic Regression Methods and their Relative Performance

Reference 23

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verified exact
arxiv_id, observed 2026-07-02T20:17:21.439569Z

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.

source=pdf_text observed=2026-06-27T20:48:09.247338Z digest=sha256:9f83b704188181a8cba52d4c8f11964ef690649420ed9e480861a25adaece0d1

Observation cc062437-538c-4ec3-ade9-f19f63122742 · inbound

Learning the Universe: The Structure of Dust Attenuation Curves in Galaxy Simulations cites this paper.

Learning the Universe: The Structure of Dust Attenuation Curves in Galaxy Simulations Contemporary Symbolic Regression Methods and their Relative Performance

Reference 216

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T02:37:34.638581Z

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.

source=arxiv_source observed=2026-06-27T15:48:32.275887Z digest=sha256:0ec88a281cb1ce3b3b8cb3f1bcfd8ba478180ddf7482f83b08c8552dbc30fad9

Observation 05305c75-ce9e-4197-8a1b-80b3d92c0d1d · inbound

Sample Complexity of Scientific Discovery: PAC Learnability of Compositional Function Trees cites this paper.

Sample Complexity of Scientific Discovery: PAC Learnability of Compositional Function Trees Contemporary Symbolic Regression Methods and their Relative Performance

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-06-30T07:54:21.869808Z

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.

source=arxiv_source observed=2026-06-30T07:52:26.378643Z digest=sha256:85487e38744cefe16c00d92a20cc903f33c524296f688e1035af8d90a59dd56b

Observation 9c8f1af1-bfbb-4f02-9dcd-e55f7080b764 · inbound

NestyNet. I. Physics Functions Are Hard to Fit with Neural Networks: A Framework for Accurate Surrogates and Analytic Derivatives cites this paper.

NestyNet. I. Physics Functions Are Hard to Fit with Neural Networks: A Framework for Accurate Surrogates and Analytic Derivatives Contemporary Symbolic Regression Methods and their Relative Performance

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T22:15:18.987743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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