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Paper Citation Record · LEDGER

Machine Learning in High Energy Physics: A review of heavy-flavor jet tagging at the LHC

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.01071.

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

pith.paper-citation-record.v1
2404.01071 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:07:26.789061Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T01:08:47.504054Z

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 9f4e7d8d-5c01-4df9-a237-b86c959ac0af · inbound

Investigation of the performance of a GNN-based b-jet tagging method in heavy-ion collisions cites this paper.

Investigation of the performance of a GNN-based b-jet tagging method in heavy-ion collisions Machine Learning in High Energy Physics: A review of heavy-flavor jet tagging at the LHC

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T22:07:26.789061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:07:26.789061Z digest=sha256:1dd261ce183b866d520b97f395519a003f1b958eb19952c26118365951ffc6fc

Observation 42811b84-52db-41d7-954a-69695605d48c · inbound

Shedding Light on Dark Matter at the LHC with Machine Learning cites this paper.

Shedding Light on Dark Matter at the LHC with Machine Learning Machine Learning in High Energy Physics: A review of heavy-flavor jet tagging at the LHC

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-04T16:19:45.832833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:19:45.832833Z digest=sha256:d88d9327c92370ed58450e3e12e252100d03ce98a4213086b7094f5ff80e246d

Observation 4905a350-f3b5-47e5-a86a-5d210cdfc90a · inbound

KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging cites this paper.

KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging Machine Learning in High Energy Physics: A review of heavy-flavor jet tagging at the LHC

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-17T01:08:47.506869Z

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.

source=pdf_text observed=2026-05-17T01:05:39.461265Z digest=sha256:778b8e0ee2323ff9a002045fe1d4c1023baa6490558409ca4071b6920d48a2c0

Observation 0d6bac55-ccfd-483b-bff5-fa88833eea90 · inbound

KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging cites this paper.

KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging Machine Learning in High Energy Physics: A review of heavy-flavor jet tagging at the LHC

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-03T18:00:46.124113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:00:46.124113Z digest=sha256:f026f94c11a8257b95508b270fcbf79f290678051d3059336e2ec11ad183842d

Observation 3c703161-f38b-4a92-923f-8ca1fbeb1773 · inbound

Simplex Demixing: Disentangling Multiple Light-Flavor Jets at Colliders cites this paper.

Simplex Demixing: Disentangling Multiple Light-Flavor Jets at Colliders Machine Learning in High Energy Physics: A review of heavy-flavor jet tagging at the LHC

Reference 49

Resolution
unresolved
no resolver link, observed 2026-07-31T05:57:08.357401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T05:57:08.357401Z digest=sha256:36ea57cc642d863a55b56754abb13923e0d010ad6854bfd9e5dffc2849e049cd