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Paper Citation Record · LEDGER

Point Cloud Transformers applied to Collider Physics

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2102.05073.

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

pith.paper-citation-record.v1
2102.05073 v2

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 2026-08-11T06:34:44.6726+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:48:01.310269Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:50:00.307408Z

Reference resolution

0 of 0 outbound references displayed

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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 069e4353-3406-4aab-8a1c-af1d48d8b07f · inbound

Generating particle physics Lagrangians with transformers cites this paper.

Generating particle physics Lagrangians with transformers Point Cloud Transformers applied to Collider Physics

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T19:48:01.310269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation dffe0bb0-72ab-4887-9e34-62578b85be6f · inbound

IAFormer: Interaction-Aware Transformer network for collider data analysis cites this paper.

IAFormer: Interaction-Aware Transformer network for collider data analysis Point Cloud Transformers applied to Collider Physics

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-22T17:14:59.563065Z

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.

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Observation 27481d46-bacf-4629-a456-91abd21d85df · 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 Point Cloud Transformers applied to Collider Physics

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-17T01:08:47.550329Z

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.

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Observation e091a318-7219-459d-be3c-fc95ad46a01f · 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 Point Cloud Transformers applied to Collider Physics

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-03T18:00:46.530271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:00:46.530271Z digest=sha256:3e8320cfbc11f24ea9da2944dae9cfc511427eb88e45e80d9b51fc9741554c16

Observation a2020509-c8a7-4ef3-be82-6e42a35c54dd · inbound

Application of Deep Learning to Jet Charge Discrimination cites this paper.

Application of Deep Learning to Jet Charge Discrimination Point Cloud Transformers applied to Collider Physics

Reference 40

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T17:50:00.308991Z

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=2026-06-25T23:26:05.669325Z digest=sha256:460defd81b91c6b8f21c5438c80895112009eeda4779c00b2f832c76c9c95c97

Observation e4bc15a5-5c65-4710-85da-b9523329f387 · inbound

Predict before you train: Scaling Laws for particle physics foundation models cites this paper.

Predict before you train: Scaling Laws for particle physics foundation models Point Cloud Transformers applied to Collider Physics

Reference 24

Resolution
unresolved
no resolver link, observed 2026-07-30T23:56:38.632404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T23:56:38.632404Z digest=sha256:501f545105b1d7ac9689a471d0a49d5bd78321dc3db7b2e694538578728ee583