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Paper Citation Record · LEDGER

Learning charges and long-range interactions from energies and forces

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.15455.

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

pith.paper-citation-record.v1
2412.15455 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:23:19.482942Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T16:14:06.257417Z

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 0739db44-dee7-4033-b2b1-e32fef659567 · inbound

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications cites this paper.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Learning charges and long-range interactions from energies and forces

Reference 127

Resolution
unresolved
no resolver link, observed 2026-08-06T22:23:19.482942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:23:19.482942Z digest=sha256:70758f3b9b9f9ade781fdf5341e418a95e766c1538a2a5fb5a79a9af0bb728d4

Observation f697515d-0c43-4937-ba37-31d0556a8ea6 · inbound

A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials cites this paper.

A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials Learning charges and long-range interactions from energies and forces

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:14:06.337480Z

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.

source=pdf_text observed=2026-08-06T16:13:54.965793Z digest=sha256:c563cd8431e5fee44a61890d6b05d90cf601948ca2a4ff2b2511ab58704a1cd4