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Paper Citation Record · LEDGER

A Language Model for Particle Tracking

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.10239.

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

pith.paper-citation-record.v1
2402.10239 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:54:10.028477Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T07:25:28.717578Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
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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 b7bc8573-970c-4819-aa70-da8322de4512 · inbound

End-to-End Multi-Track Reconstruction using Graph Neural Networks at Belle II cites this paper.

End-to-End Multi-Track Reconstruction using Graph Neural Networks at Belle II A Language Model for Particle Tracking

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-12T18:11:53.529160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:11:53.529160Z digest=sha256:65d5923e35d4aa8c6d7a5b116cf6bdf462f825f72541e3c08bea2c706ae00dc4

Observation cb7efad5-51de-4aef-88fc-49226607e266 · inbound

Pretrained Event Classification Model for High Energy Physics Analysis cites this paper.

Pretrained Event Classification Model for High Energy Physics Analysis A Language Model for Particle Tracking

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-23T07:25:28.719544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-23T07:22:50.166479Z digest=sha256:0b59010bdffec7742d05b862601a60978f0776c57f2f5db168353fd81d3d136e

Observation cc1ad3d3-2ba0-4899-abe7-cca643ca0cff · inbound

Pretrained Event Classification Model for High Energy Physics Analysis cites this paper.

Pretrained Event Classification Model for High Energy Physics Analysis A Language Model for Particle Tracking

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T15:47:54.671892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:47:54.671892Z digest=sha256:3a329867153fcb7958edb9e73b9d849935dbece9ec5d43e2e40578f82fac56fd

Observation 9adcf2ae-3a5c-4b5a-8714-6489f5e0596d · inbound

Towards Foundation Models for Experimental Readout Systems Combining Discrete and Continuous Data cites this paper.

Towards Foundation Models for Experimental Readout Systems Combining Discrete and Continuous Data A Language Model for Particle Tracking

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-15T21:54:10.028477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:54:10.028477Z digest=sha256:ada7b1f015aabafb0155f11ef4f81e799c5f1cbe6654b79ffb8c4d7eedd25147

Observation 108dc886-931a-49d3-8948-f22cc563ac14 · inbound

Transformer-Based Approach to Enhance Positron Tracking Performance in MEG II cites this paper.

Transformer-Based Approach to Enhance Positron Tracking Performance in MEG II A Language Model for Particle Tracking

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-03T14:45:03.444256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:45:03.444256Z digest=sha256:f7d8943e1e6c2d23d887cecf645bba79a3f9feb8051d855bd2b7e4e5f387a570

Observation 0f2909f8-5a58-4642-81ad-699bc88e7c71 · 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 A Language Model for Particle Tracking

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-01T21:19:39.035179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T21:19:39.035179Z digest=sha256:e224b77c6a0435da89a80186562dac804086b687cb848464586617ccd8ce5ca1