Paper Citation Record · LEDGER

Graph Neural Networks in Particle Physics

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2007.13681.

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

pith.paper-citation-record.v1
2007.13681 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 2026-08-16T06:30:59.297886+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:15:54.733418Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T03:28:57.800406Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

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 401c56b9-e5d1-4e3f-b588-10ab02e217fc · inbound

Interpreting Transformers for Jet Tagging cites this paper.

Interpreting Transformers for Jet Tagging Graph Neural Networks in Particle Physics

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T22:17:30.755749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fc08213-30ad-47e4-9808-442492481e6a · inbound

Tagging fully hadronic exotic decays of the vectorlike $\mathbf{B}$ quark using a graph neural network cites this paper.

Tagging fully hadronic exotic decays of the vectorlike $\mathbf{B}$ quark using a graph neural network Graph Neural Networks in Particle Physics

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T22:15:54.733418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcba2aa5-73d4-432f-9968-cefb4b1a839c · inbound

Learning to Reconstruct: A Differentiable Approach to Muon Tracking at the LHC cites this paper.

Learning to Reconstruct: A Differentiable Approach to Muon Tracking at the LHC Graph Neural Networks in Particle Physics

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-17T03:28:57.802934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4f72cf91-59d8-45c7-99e7-80a0b9f834ab · inbound

Learning Standard Model structure from LHC data with Riemannian flow matching cites this paper.

Learning Standard Model structure from LHC data with Riemannian flow matching Graph Neural Networks in Particle Physics

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T21:19:36.257787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.