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Paper Citation Record · LEDGER

Fast multilabel classification of HEP constraints with deep learning

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.05453.

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

pith.paper-citation-record.v1
2409.05453 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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:20:33.804093Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T05:20:34.599999Z

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 e0017cc4-6dee-45e0-9829-845fb3c7bb11 · inbound

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology cites this paper.

hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology Fast multilabel classification of HEP constraints with deep learning

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-11T05:20:34.604508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T05:20:33.804093Z digest=sha256:ea36e0b12c9d3a929bf3e0a4dd5104634b0fcf2015be9d5858a93ac6358aa20f

Observation 8749d36c-6b0a-4a87-8940-fe5e0158d6f0 · inbound

Normalizing Flow-Assisted Nested Sampling on Type-II Seesaw Model cites this paper.

Normalizing Flow-Assisted Nested Sampling on Type-II Seesaw Model Fast multilabel classification of HEP constraints with deep learning

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T13:21:25.331599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T13:21:25.331599Z digest=sha256:a24a087884e1b516089ebe59b082565d30e247456b1574fa09ce8e8cadce403b