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Paper Citation Record · LEDGER

Physics and Computing Performance of the EggNet Tracking Pipeline

As of 10 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2506.03415.

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

pith.paper-citation-record.v1
2506.03415 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:09:20.538044Z

measured 19 of 19 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

19 of 19 outbound references displayed

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  • verified fuzzy6
  • unresolved11
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4f19adc6-0b5c-4536-b668-8e19b7501b4b · outbound

This paper cites Strandlie, R.

Physics and Computing Performance of the EggNet Tracking Pipeline Strandlie, R

Reference 1

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no resolver link, observed 2026-08-07T11:09:18.686792Z

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source=pdf_text observed=2026-08-07T11:09:18.686792Z digest=sha256:13f72c32bd8d8254c76e41fd3f543bd9b3df8f766823ce935af77fe49d0a6cd5

Observation 9561bc59-36a2-4e8e-8c15-a906b6cf5a80 · outbound

This paper cites Performance of the ATLAS Track Reconstruction Algorithms in Dense Environments in LHC Run 2.

Physics and Computing Performance of the EggNet Tracking Pipeline Performance of the ATLAS Track Reconstruction Algorithms in Dense Environments in LHC Run 2

Reference 2

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source=pdf_text observed=2026-08-07T11:09:18.751448Z digest=sha256:d7063a9006ad8af7a824ca53e16f39c4b64020d7bdb36ba952bae554efb3401e

Observation 7e247bda-d1eb-4e21-95fb-258e2d253613 · outbound

This paper cites Description and performance of track and primary-vertex reconstruction with the CMS tracker.

Physics and Computing Performance of the EggNet Tracking Pipeline Description and performance of track and primary-vertex reconstruction with the CMS tracker

Reference 3

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source=pdf_text observed=2026-08-07T11:09:18.825369Z digest=sha256:d50b6bae6e6812039823331ad0de97cadf9525011ef4af33b01d8eeb4611ec01

Observation 72a753b4-162d-41d3-bfe3-bd41e24f5c55 · outbound

This paper cites Performance of a Geometric Deep Learning Pipeline for HL-LHC Particle Tracking.

Physics and Computing Performance of the EggNet Tracking Pipeline Performance of a Geometric Deep Learning Pipeline for HL-LHC Particle Tracking

Reference 4

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source=pdf_text observed=2026-08-07T11:09:18.881330Z digest=sha256:53864a9138d2e6c74757cdf8eab32c1fed7a6d47353644642d54dd8770877d93

Observation a63cdf4c-4954-417d-93bb-ebeaa84d4506 · outbound

This paper cites Towards a realistic track reconstruction algorithm based on graph neural networks for the HL-LHC.

Physics and Computing Performance of the EggNet Tracking Pipeline Towards a realistic track reconstruction algorithm based on graph neural networks for the HL-LHC

Reference 5

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source=pdf_text observed=2026-08-07T11:09:18.954097Z digest=sha256:6c47c124e8fd33eebfb89f4bacdc053abcfa64970001ef80db01945a3d46f507

Observation 0cebab7c-9c66-4eaa-aa60-4b6f705da1b1 · outbound

This paper cites Caillou, P.

Physics and Computing Performance of the EggNet Tracking Pipeline Caillou, P

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-07T11:09:22.453719Z

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=2026-08-07T11:09:19.092726Z digest=sha256:1ba0e473cc9f5f4ff2dd3e19b03528c96e29f80547aba2f17c185c7b5bc23513

Observation c4e16c82-d551-4eb3-a4de-677e04212f6c · outbound

This paper cites High Pileup Particle Tracking with Object Condensation.

Physics and Computing Performance of the EggNet Tracking Pipeline High Pileup Particle Tracking with Object Condensation

Reference 7

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source=pdf_text observed=2026-08-07T11:09:19.200031Z digest=sha256:4e5ad678edb62bd330fce888d2bfd418eb5228285dff53817170395ae42a9b2c

Observation 880ecdd1-e537-4ec0-9f69-2b3c482ae58b · outbound

This paper cites Accelerating the Inference of the Exa.TrkX Pipeline.

Physics and Computing Performance of the EggNet Tracking Pipeline Accelerating the Inference of the Exa.TrkX Pipeline

Reference 8

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local_arxiv, observed 2026-08-07T11:09:20.872690Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T11:09:19.310129Z digest=sha256:9e67ed2225c3448d9a47c2804ca8b5eac572222c53c0fd87c95c4bda81882a89

Observation 40b663ea-acb1-462b-8b97-ed8421049e62 · outbound

This paper cites EggNet: An Evolving Graph-based Graph Attention Network for Particle Track Reconstruction.

Physics and Computing Performance of the EggNet Tracking Pipeline EggNet: An Evolving Graph-based Graph Attention Network for Particle Track Reconstruction

Reference 9

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source=pdf_text observed=2026-08-07T11:09:19.417320Z digest=sha256:6587a93df9b6993760b1ee58f23d5075eb851f2769e7c0ff5b4c8a0cd95ed0f6

Observation 4564f13a-a965-44a6-9b7d-f0d040e43223 · outbound

This paper cites The Tracking Machine Learning challenge : Accuracy phase.

Physics and Computing Performance of the EggNet Tracking Pipeline The Tracking Machine Learning challenge : Accuracy phase

Reference 10

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source=pdf_text observed=2026-08-07T11:09:19.516719Z digest=sha256:562cb11ae87e2df463b35de381f783b84dde6931e0b7bce9c8a37fb655da3b49

Observation 1b59fb74-7a38-45c6-a80c-6e4e0a1df501 · outbound

This paper cites The Tracking Machine Learning challenge : Throughput phase.

Physics and Computing Performance of the EggNet Tracking Pipeline The Tracking Machine Learning challenge : Throughput phase

Reference 11

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source=pdf_text observed=2026-08-07T11:09:19.642567Z digest=sha256:39cd6d5980aa5e68665a06d868159ebf0011b6881650bfc8081b63fa0bc7d944

Observation 69eb1edd-f2b5-458a-8dad-440aa7db7df3 · outbound

This paper cites Ester, H.P.

Physics and Computing Performance of the EggNet Tracking Pipeline Ester, H.P

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-07T11:09:22.222785Z

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=2026-08-07T11:09:19.762996Z digest=sha256:fdc4b07414c3e6c150bf16670277a042a2d36baa3b30c6897db1e9faff8aa606

Observation 2a947d75-4e86-445e-a88e-bdf17a8a4eca · outbound

This paper cites Elfwing, E.

Physics and Computing Performance of the EggNet Tracking Pipeline Elfwing, E

Reference 13

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source=pdf_text observed=2026-08-07T11:09:19.878339Z digest=sha256:a2cac9acf86f18ef44d860e88a61df14eb6933a43145549d7ae05002f7bdf916

Observation acffb3e2-6f7d-449e-8c7a-1de2d2391832 · outbound

This paper cites Layer Normalization.

Physics and Computing Performance of the EggNet Tracking Pipeline Layer Normalization

Reference 14

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source=pdf_text observed=2026-08-07T11:09:20.008552Z digest=sha256:920d12be780de392e0a970682674df1431dee53623e0cb982b3fcbfe277c63b3

Observation c9432c27-7fd7-4e1f-873b-5cf19a4f4cac · outbound

This paper cites Paszke, S.

Physics and Computing Performance of the EggNet Tracking Pipeline Paszke, S

Reference 15

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raw_fallback, observed 2026-08-07T11:09:21.950975Z

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=2026-08-07T11:09:20.097087Z digest=sha256:0d9459b98685ba653519b0396444bc99747758918726ca540ec30624d4b65260

Observation 1a71d318-11ba-4c12-9334-ddfaf6a03a68 · outbound

This paper cites Falcon, The PyTorch Lightning team, PyTorch Lightning (2019),https:// github.com/Lightning-AI/lightning.

Physics and Computing Performance of the EggNet Tracking Pipeline Falcon, The PyTorch Lightning team, PyTorch Lightning (2019),https:// github.com/Lightning-AI/lightning

Reference 16

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raw_fallback, observed 2026-08-07T11:09:21.660976Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T11:09:20.196655Z digest=sha256:67fc73ff455f60eb3b3e2a4276af19750f42d33a3f511c2e4dbbd10790932003

Observation fd06198e-b7b7-4a53-ab4d-002e571e9e96 · outbound

This paper cites Atkinson, S.

Physics and Computing Performance of the EggNet Tracking Pipeline Atkinson, S

Reference 17

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raw_fallback, observed 2026-08-07T11:09:21.414268Z

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=2026-08-07T11:09:20.302586Z digest=sha256:25ef7a03f9bde64e15311b48a9ce0e4d869f27882a07143d3f91c13b9ff4e5c1

Observation a49cf7ca-2f65-4108-86d4-49f283095e1e · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Physics and Computing Performance of the EggNet Tracking Pipeline Adam: A Method for Stochastic Optimization

Reference 18

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source=pdf_text observed=2026-08-07T11:09:20.398008Z digest=sha256:5f2053a436ee75f69ea152e97912dbd855ab0be6314185510d09dc62c018d440

Observation 3914c4da-bb5c-44f2-9988-000d8ca4a301 · outbound

This paper cites Team, RAPIDS: Libraries for End to End GPU Data Science (2023),https: //rapids.ai.

Physics and Computing Performance of the EggNet Tracking Pipeline Team, RAPIDS: Libraries for End to End GPU Data Science (2023),https: //rapids.ai

Reference 19

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Pith citing papers

No inbound Pith citation observations are available.