Paper Citation Record · LEDGER

Building Hadron Potentials from Lattice QCD with Deep Neural Networks

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.03082.

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

pith.paper-citation-record.v1
2410.03082 v1

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 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:57:49.829873Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T12:14:52.278228Z

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 4d79a348-bbe1-4259-990a-a2f56e459b17 · inbound

Deep learning for exploring hadron-hadron interactions cites this paper.

Deep learning for exploring hadron-hadron interactions Building Hadron Potentials from Lattice QCD with Deep Neural Networks

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T22:57:49.829873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7d96e52-b6e5-421e-838a-4691a4233bbb · inbound

Physics-Driven Learning for Inverse Problems in Quantum Chromodynamics cites this paper.

Physics-Driven Learning for Inverse Problems in Quantum Chromodynamics Building Hadron Potentials from Lattice QCD with Deep Neural Networks

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-10T21:15:54.591773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34cfb874-4ab9-4be9-b0f3-69fc1b9b9287 · inbound

Towards constraining QCD phase transitions in neutron star interiors: Bayesian Inference with TOV linear response analysis cites this paper.

Towards constraining QCD phase transitions in neutron star interiors: Bayesian Inference with TOV linear response analysis Building Hadron Potentials from Lattice QCD with Deep Neural Networks

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T14:01:08.807964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7ad100f-fe02-4d20-ba4d-d8305b6e6e15 · inbound

Neural network extraction of chromo-electric and chromo-magnetic gluon masses cites this paper.

Neural network extraction of chromo-electric and chromo-magnetic gluon masses Building Hadron Potentials from Lattice QCD with Deep Neural Networks

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-06T12:14:52.282865Z

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.