Paper Citation Record · LEDGER

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors

As of 20 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2504.17272.

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

pith.paper-citation-record.v1
2504.17272 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:50:02.598520Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

verified exact0
verified fuzzy16
unresolved3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 94332540-11a5-4edc-b723-5a679f71d0d4 · outbound

This paper cites Novel 3-D clustering algorithm and two particle separation with tile HCAL.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Novel 3-D clustering algorithm and two particle separation with tile HCAL

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.836696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4e8bda14-d95c-4364-932e-ab3dcaf33c28 · outbound

This paper cites [CALICE] Separation of two electromagnetic or electromagnetic-hadronic showers in CALICE SiW ECAL and ILD.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors [CALICE] Separation of two electromagnetic or electromagnetic-hadronic showers in CALICE SiW ECAL and ILD

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.823835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 854e7d6e-a113-4efe-abb7-792c0bf7d3f7 · outbound

This paper cites Artificial Neural Networks on FPGAs for Real-Time Energy Reconstruction of the ATLAS LAr Calorimeters.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Artificial Neural Networks on FPGAs for Real-Time Energy Reconstruction of the ATLAS LAr Calorimeters

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.812456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 408e65a2-042e-415c-8af1-9cbac06729a3 · outbound

This paper cites Axiomatic attribution for deep networks.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Axiomatic attribution for deep networks

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.798439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fbdc529a-078d-484a-abfe-79c1ab8d52fa · outbound

This paper cites SmoothGrad: removing noise by adding noise.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors SmoothGrad: removing noise by adding noise

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:02.549547Z

Source-reported events for the cited work

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Observation 15c89544-8e35-4420-afed-e3ddcfa0d3eb · outbound

This paper cites Occlusion Sensitivity Analysis with Augmentation Subspace Perturbation in Deep Feature Space.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Occlusion Sensitivity Analysis with Augmentation Subspace Perturbation in Deep Feature Space

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.786807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ce052c1e-acb2-4166-8a0d-715b65f3f6e5 · outbound

This paper cites Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T10:50:02.557186Z

Source-reported events for the cited work

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Observation 06cc6531-d6a4-4679-b301-6ce640336768 · outbound

This paper cites TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.776652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f0b9b445-6ba3-47fb-9f69-57e8900c167e · outbound

This paper cites an unresolved cited work.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:50:02.766134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 74f584be-8c2d-44a1-b93e-ed43ad5fe0b4 · outbound

This paper cites Matplotlib: A 2D Graphics Environment.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Matplotlib: A 2D Graphics Environment

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.755464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ce61d5b-7e84-4eb3-80b7-5e606b0d17a5 · outbound

This paper cites ROOT: An object oriented data analysis framework.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors ROOT: An object oriented data analysis framework

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.744477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7a142206-c600-407d-97bf-1e814dfbd393 · outbound

This paper cites Visualkeras.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Visualkeras

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.734207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 57ea5953-0261-4402-bbf9-c6a74da697f3 · outbound

This paper cites Using Artificial Intelligence in the Reconstruction of Signals from the PADME Electromag- netic Calorimeter.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Using Artificial Intelligence in the Reconstruction of Signals from the PADME Electromag- netic Calorimeter

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.722886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 520876a3-8aec-4b38-b9b0-c8d6cb4af726 · outbound

This paper cites Pattern recognition and signal parameters extraction using machine learning methods.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Pattern recognition and signal parameters extraction using machine learning methods

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.710516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 00a30583-8679-4870-a17f-8c5414183bfe · outbound

This paper cites Convolutional Autoencoders for Signal Reconstruction and their Application to Damage Signature Extraction.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Convolutional Autoencoders for Signal Reconstruction and their Application to Damage Signature Extraction

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.696860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation dac024ad-4c46-4ca3-8ac0-27435f61a2ad · outbound

This paper cites 6; V1751 Technical Information Manual Rev.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors 6; V1751 Technical Information Manual Rev

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.685553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 170ea130-42e8-459b-92fa-04cf6da0a074 · outbound

This paper cites Machine learning assisted reconstruction of positron-on-target annihilation events in the PADME experiment.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Machine learning assisted reconstruction of positron-on-target annihilation events in the PADME experiment

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.674541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation dc244fc4-2c68-4253-9779-320f7b15998c · outbound

This paper cites Applicability evaluation of selected xAI methods for machine learning algorithms for signal parameters extraction.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Applicability evaluation of selected xAI methods for machine learning algorithms for signal parameters extraction

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.663295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6f688f6d-2100-4832-aeb8-c582e88b8a64 · outbound

This paper cites Visualizing and Understanding Convolutional Networks.

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors Visualizing and Understanding Convolutional Networks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:50:02.652280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.