Paper Citation Record · LEDGER

SYMBA: Symbolic Computation of Squared Amplitudes in High Energy Physics with Machine Learning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2206.08901.

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

pith.paper-citation-record.v1
2206.08901 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:26:33.760300Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T06:47:43.321360Z

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 578bea2b-607a-4a3c-9d9a-3cf5254f2c0b · inbound

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

$\mathcal{CP}$-Analyses with Symbolic Regression SYMBA: Symbolic Computation of Squared Amplitudes in High Energy Physics with Machine Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T19:26:33.760300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7ea024a-e38a-48d5-82fe-ffd5cc825f55 · inbound

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency cites this paper.

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency SYMBA: Symbolic Computation of Squared Amplitudes in High Energy Physics with Machine Learning

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-03T15:47:05.861274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97b9dc2f-33a4-4181-ac82-12478b87be65 · inbound

A Novel Implementation of the Matrix Element Method at Next-to-Leading Order for the Measurement of the Higgs Self-Coupling ${\lambda}_{3H}$ cites this paper.

A Novel Implementation of the Matrix Element Method at Next-to-Leading Order for the Measurement of the Higgs Self-Coupling ${\lambda}_{3H}$ SYMBA: Symbolic Computation of Squared Amplitudes in High Energy Physics with Machine Learning

Reference 37

Resolution: malformed identifier; no resolver link, observed 2026-08-03T05:27:31.706713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0310747d-d2c7-417b-bf2e-23ff495c26b4 · inbound

Efficient AI-Inspired Reduction of Feynman Integrals via Tube Seeding cites this paper.

Efficient AI-Inspired Reduction of Feynman Integrals via Tube Seeding SYMBA: Symbolic Computation of Squared Amplitudes in High Energy Physics with Machine Learning

Reference 82

Resolution: verified exact; arxiv_id, observed 2026-07-03T06:47:43.322675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.