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Paper Citation Record · LEDGER

Interpretable deep learning models for the inference and classification of LHC data

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.12330.

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

pith.paper-citation-record.v1
2312.12330 v2

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 2026-08-06T16:29:11.865569Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:29:54.698074Z

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 3c232322-7295-495e-9ece-f54ffa66dde3 · inbound

Theory-informed neural networks for particle physics cites this paper.

Theory-informed neural networks for particle physics Interpretable deep learning models for the inference and classification of LHC data

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T16:29:11.865569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:29:11.865569Z digest=sha256:09eb533095388b15fd5b7297081a22a48d23ad2f05284cc2b667b7b10a57f3ef

Observation 12359bfb-094b-4e9d-9e98-d855a56b96c9 · inbound

Toward an event-level analysis of hadron structure using differential programming cites this paper.

Toward an event-level analysis of hadron structure using differential programming Interpretable deep learning models for the inference and classification of LHC data

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:29:54.704444Z

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=2026-08-06T15:29:53.278114Z digest=sha256:f93a0ad6b9602e2ccc990d15fecc63fe4c07745fde5fbf8d8b80bcca63d2b659