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Paper Citation Record · LEDGER

Machine Learning in the Search for New Fundamental Physics

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2112.03769.

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

pith.paper-citation-record.v1
2112.03769 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:16:18.730450Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T19:38:53.000850Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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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 9304c45a-1966-457e-b366-ace0a0667462 · inbound

Generator Based Inference (GBI) cites this paper.

Generator Based Inference (GBI) Machine Learning in the Search for New Fundamental Physics

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T12:16:18.730450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:16:18.730450Z digest=sha256:6a92a5767fed595ac20b184b0aaece999702b7f5a2a3e4e7d2ce2bbfee054acc

Observation 9869ea77-adf6-463f-a976-e69ce7afa4e8 · 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 the Search for New Fundamental Physics

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-04T16:19:45.259928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:19:45.259928Z digest=sha256:70abc845afd0fa1713c55dbc417ff39dc27244882f262c12ff6c64770f47f9b2

Observation a85552e9-24c6-415e-ad16-723894fe9ea7 · inbound

Optimal Transport Event Representation for Anomaly Detection cites this paper.

Optimal Transport Event Representation for Anomaly Detection Machine Learning in the Search for New Fundamental Physics

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-03T18:35:49.612847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:35:49.612847Z digest=sha256:e35586874b48b6950f750ef9a51129fc512a7ba99498c1a63db91cb28eafd09d

Observation 62a31620-6dad-4180-94d6-f39371373444 · inbound

Look everywhere effects in anomaly detection cites this paper.

Look everywhere effects in anomaly detection Machine Learning in the Search for New Fundamental Physics

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-03T16:25:10.490864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:25:10.490864Z digest=sha256:f1fa898df77a86ff9e8cb215b4a55c198c851c9ac85463e1afaf63178fb1268d

Observation 2935d3a4-39bb-41aa-a1b2-e5480e4750e9 · inbound

Explicit or Implicit? Encoding Physics at the Precision Frontier cites this paper.

Explicit or Implicit? Encoding Physics at the Precision Frontier Machine Learning in the Search for New Fundamental Physics

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-03T02:35:28.691008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T02:35:28.691008Z digest=sha256:fd2fe1c796c6e3e399b356b5ea6f567dc48333e1bec1b048c3f877f170c5b32b

Observation 42fd6e32-3902-42c2-ade8-d110d59a207e · inbound

Probing Proton Structure via Physics-Guided Neural Networks in Holographic QCD cites this paper.

Probing Proton Structure via Physics-Guided Neural Networks in Holographic QCD Machine Learning in the Search for New Fundamental Physics

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-13T18:48:08.205276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T18:44:28.360549Z digest=sha256:847c70ad07689ab40a8f991fe4560af31c6665cf8e4f13bd4bc9164a9c770028

Observation 7f41b43e-a49b-428c-b058-d71e71e87069 · inbound

Lund Plane to Bloch (LP2B) Encoding for Object and Polarization Tagging with Quantum Jet Substructure cites this paper.

Lund Plane to Bloch (LP2B) Encoding for Object and Polarization Tagging with Quantum Jet Substructure Machine Learning in the Search for New Fundamental Physics

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:25:26.655663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T13:20:58.270447Z digest=sha256:0c7a31a2873d920a02dbfad7e8a7c3c43b6bacac4dade6f1603612076885d74f

Observation 903dca86-aa01-4845-ac75-d47047eb17bc · inbound

Probing lepton flavor mixing in $W_R$ searches with machine learning at the LHC cites this paper.

Probing lepton flavor mixing in $W_R$ searches with machine learning at the LHC Machine Learning in the Search for New Fundamental Physics

Reference 36

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T04:16:35.607631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T09:17:10.438805Z digest=sha256:1c49731c4bf978512018734e2a975ffd3c0430dbf1ecedc1d450d40f674b2034

Observation 6dfde818-5557-44f6-8c55-0ff3b8e0c304 · inbound

EasyScan_HEP 2: Agent-Ready Parameter Scans for High-Energy Physics cites this paper.

EasyScan_HEP 2: Agent-Ready Parameter Scans for High-Energy Physics Machine Learning in the Search for New Fundamental Physics

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-01T10:45:42.231692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-01T05:14:01.342230Z digest=sha256:e5b830af8ad4c337ccec46d93f0d6a5958b7ce306b49fb4eebb96fd375810aac

Observation 32428e56-1314-4ec0-9bd1-1798c58a98a6 · inbound

Local Conformal Predictions for Calibrated Surrogates cites this paper.

Local Conformal Predictions for Calibrated Surrogates Machine Learning in the Search for New Fundamental Physics

Reference 266

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T19:38:53.002526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-07-03T19:29:34.070294Z digest=sha256:3dfef31d2915524ee623472c1b63c13a3ee8c22142ec728cc15ceb4b6579c8fe

Observation 215686bc-ac5d-443f-8f7c-8239cc2a2182 · inbound

Heavy-Flavor Electron Classification Using Hadronic Environment as Point Cloud cites this paper.

Heavy-Flavor Electron Classification Using Hadronic Environment as Point Cloud Machine Learning in the Search for New Fundamental Physics

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-03T02:57:34.523419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-03T02:49:47.373673Z digest=sha256:2de6f29c4700737640169c479c28663fa51dc2248ea3d6450079ba0576fe20af

Observation b8b4a62e-d40b-48dc-8745-14b246a5d444 · inbound

Learning Standard Model structure from LHC data with Riemannian flow matching cites this paper.

Learning Standard Model structure from LHC data with Riemannian flow matching Machine Learning in the Search for New Fundamental Physics

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-01T21:19:40.459588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T21:19:40.459588Z digest=sha256:da636d021a198ec0e4e88127e7382700cddb63ae3c9c7f51c7f230dc54da35e5