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Paper Citation Record · LEDGER

Machine-learning based particle-flow algorithm in CMS

As of 16 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2508.20541.

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

pith.paper-citation-record.v1
2508.20541 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:48:48.701906Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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.

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Reference resolution

16 of 16 outbound references displayed

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  • verified fuzzy1
  • unresolved13
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e6e423d7-6587-4ba6-9213-3be15ed8e963 · outbound

This paper cites Particle-flow reconstruction and global event description with the CMS detector.

Machine-learning based particle-flow algorithm in CMS Particle-flow reconstruction and global event description with the CMS detector

Reference 1

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Observation 504c3e09-6b52-45ec-9f99-dfca755e1230 · outbound

This paper cites The CMS experiment at the CERN LHC.

Machine-learning based particle-flow algorithm in CMS The CMS experiment at the CERN LHC

Reference 2

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source=pdf_text observed=2026-08-15T16:48:48.524686Z digest=sha256:0b98b42f72ade2e5fcaf687de4cf1c02d14502a985c28168c3f35627c7e2e6d1

Observation 584d15d1-d186-4797-9610-fe1b51809a85 · outbound

This paper cites Development of the CMS detector for the CERN LHC Run 3.

Machine-learning based particle-flow algorithm in CMS Development of the CMS detector for the CERN LHC Run 3

Reference 3

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Observation 1caea30b-9b0b-462b-83ff-4b254e768d91 · outbound

This paper cites Geant4 – a simulation toolkit.

Machine-learning based particle-flow algorithm in CMS Geant4 – a simulation toolkit

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-15T16:48:49.674396Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:48:48.546934Z digest=sha256:59c12b59b97bd2f253060821d680bd54f9f64ee689311d047f7763799f1a5490

Observation 3b909b63-32e6-4e30-bda3-016d8ab5723a · outbound

This paper cites Geant4 developments and applications.

Machine-learning based particle-flow algorithm in CMS Geant4 developments and applications

Reference 5

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source=pdf_text observed=2026-08-15T16:48:48.557102Z digest=sha256:7f09ecff78f5cfc783e703cc2a362200f92fd9fd39abd745c100e5e75a518157

Observation 980c74ce-5f16-4107-b800-4f72b6132f56 · outbound

This paper cites Recent developments inGeant4.

Machine-learning based particle-flow algorithm in CMS Recent developments inGeant4

Reference 6

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source=pdf_text observed=2026-08-15T16:48:48.570730Z digest=sha256:ce454684d1539c9f532d6d96aa38db491adc46fd4a1d2c999727ff45438ebf5d

Observation ee8b37e3-55f4-4ac3-bfa8-5ab3638b632b · outbound

This paper cites A comprehensive guide to the physics and usage of PYTHIA 8.3.

Machine-learning based particle-flow algorithm in CMS A comprehensive guide to the physics and usage of PYTHIA 8.3

Reference 7

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source=pdf_text observed=2026-08-15T16:48:48.582548Z digest=sha256:b4eff3eaf64b4d37bfdfc116d25fc2fb596fbfa4427a383e0e30b697a31d4afe

Observation 31a24eff-7334-4fce-91f6-137d5f286056 · outbound

This paper cites Extraction and validation of a new set of CMS PYTHIA8 tunes from underlying-event measurements.

Machine-learning based particle-flow algorithm in CMS Extraction and validation of a new set of CMS PYTHIA8 tunes from underlying-event measurements

Reference 8

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source=pdf_text observed=2026-08-15T16:48:48.593576Z digest=sha256:9df48ffb1bfa6e4d88e0bea873a99916f5f749b560c490511d5716777862357f

Observation 637448dc-ecd6-4fd6-be15-74d336de4160 · outbound

This paper cites MLPF: Efficient machine-learned particle-flow reconstruction using graph neural networks.

Machine-learning based particle-flow algorithm in CMS MLPF: Efficient machine-learned particle-flow reconstruction using graph neural networks

Reference 9

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Observation decd80a4-c6bf-4eba-bee5-28633b95d835 · outbound

This paper cites Machine Learning for Particle Flow Reconstruction at CMS.

Machine-learning based particle-flow algorithm in CMS Machine Learning for Particle Flow Reconstruction at CMS

Reference 10

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local_arxiv, observed 2026-08-15T16:48:49.262873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:48:48.612529Z digest=sha256:9e9bebf498ce43901f5dd608d3ae9540a19732c5fd8bf2c45e17e3592be52ad6

Observation 91c0d46b-2339-4dbe-9675-bc452e090188 · outbound

This paper cites Progress towards an improved particle flow algorithm at CMS with machine learning.

Machine-learning based particle-flow algorithm in CMS Progress towards an improved particle flow algorithm at CMS with machine learning

Reference 11

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local_arxiv, observed 2026-08-15T16:48:49.203089Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:48:48.625288Z digest=sha256:3ff9e8a90c40c0c44c53f62267c62221ce547ab022f69dd1be2b9c9bc81e8ffa

Observation 6582a03c-5072-4a95-9299-292dc00682b8 · outbound

This paper cites FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.

Machine-learning based particle-flow algorithm in CMS FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Reference 12

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source=pdf_text observed=2026-08-15T16:48:48.641083Z digest=sha256:687235fecd9ce7bb69c602bec3e854fc65a2b7d96808352e3dd2ecfdac1d07a3

Observation 5e064838-5dbc-41e5-baf7-c973e6af4ff2 · outbound

This paper cites Focal Loss for Dense Object Detection.

Machine-learning based particle-flow algorithm in CMS Focal Loss for Dense Object Detection

Reference 13

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source=pdf_text observed=2026-08-15T16:48:48.649084Z digest=sha256:b4935519912f3195fd7be789f1ee317ba16bae4f8f5c0c4526d8c43bdd70cad5

Observation aff8093a-7002-4915-9bdd-4d6df634744d · outbound

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

Machine-learning based particle-flow algorithm in CMS Description and performance of track and primary-vertex reconstruction with the CMS tracker

Reference 14

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Observation 74c4d615-cd33-4f32-b500-f8814d8ef15b · outbound

This paper cites Pileup mitigation at CMS in 13 TeV data.

Machine-learning based particle-flow algorithm in CMS Pileup mitigation at CMS in 13 TeV data

Reference 15

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source=pdf_text observed=2026-08-15T16:48:48.676023Z digest=sha256:e6f22d0faaea536a78b9b0246a97f35038cc1bcec2ad3e059b84b48970cc6e0a

Observation ee1ec83c-06ab-4377-8b7a-62b8f55e5a45 · outbound

This paper cites Pileup Per Particle Identification.

Machine-learning based particle-flow algorithm in CMS Pileup Per Particle Identification

Reference 16

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source=pdf_text observed=2026-08-15T16:48:48.701906Z digest=sha256:8b56b6499c3d996db1a2fed78e94b628192788a5a7569d9be4d8255b8b8ed829

Pith citing papers

No inbound Pith citation observations are available.