Paper Citation Record · LEDGER

Pathwise Explanation of ReLU Neural Networks

As of 21 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2506.18037.

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

pith.paper-citation-record.v1
2506.18037 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:03:52.176092Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

31 of 31 outbound references displayed

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verified fuzzy18
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External citation measurements

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Outbound references

Observation 6a3ba055-fd5e-47c3-8879-0ce08b51cf0e · outbound

This paper cites Peeking inside the black-box: a survey on explainable artificial intelligence ( XAI ).

Pathwise Explanation of ReLU Neural Networks Peeking inside the black-box: a survey on explainable artificial intelligence ( XAI )

Reference 1

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Observation 74517d1e-ea35-412f-946a-07596aec4b37 · outbound

This paper cites Explainable A rtificial I ntelligence ( XAI ): Concepts, taxonomies, opportunities and challenges toward responsible ai.

Pathwise Explanation of ReLU Neural Networks Explainable A rtificial I ntelligence ( XAI ): Concepts, taxonomies, opportunities and challenges toward responsible ai

Reference 2

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Observation c72bbf75-9fb0-422d-b67c-fc1931d845cc · outbound

This paper cites On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation.

Pathwise Explanation of ReLU Neural Networks On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation

Reference 3

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Observation 33e5401e-0240-41f5-8d2b-3f029342ff18 · outbound

This paper cites Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission.

Pathwise Explanation of ReLU Neural Networks Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission

Reference 4

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Observation 98f40547-27b7-4e64-9f05-a05cb6036549 · outbound

This paper cites Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey.

Pathwise Explanation of ReLU Neural Networks Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey

Reference 5

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Observation 1577ce47-6a0d-455f-a128-92aeadda9c61 · outbound

This paper cites Deep learning.

Pathwise Explanation of ReLU Neural Networks Deep learning

Reference 6

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Observation 33e68603-758d-4479-abc5-fecc13046ba8 · outbound

This paper cites DARPA ’s explainable artificial intelligence ( XAI ) program.

Pathwise Explanation of ReLU Neural Networks DARPA ’s explainable artificial intelligence ( XAI ) program

Reference 7

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Observation 5ba84fba-51de-4276-8819-e698de0e07c8 · outbound

This paper cites XAI — E xplainable artificial intelligence.

Pathwise Explanation of ReLU Neural Networks XAI — E xplainable artificial intelligence

Reference 8

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Observation 1f0d28e8-e5bd-45f8-bdef-e0562df206c6 · outbound

This paper cites Deep residual learning for image recognition.

Pathwise Explanation of ReLU Neural Networks Deep residual learning for image recognition

Reference 9

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Observation d6ac596c-0d43-4785-9de8-c3d295cb3f7a · outbound

This paper cites Learning multiple layers of features from tiny images.

Pathwise Explanation of ReLU Neural Networks Learning multiple layers of features from tiny images

Reference 10

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Source-reported events for the cited work

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Observation fb32f9ec-f943-4d33-a541-e124ae251021 · outbound

This paper cites a ldchen, Alexander Binder, Gr \'e goire Montavon, Wojciech Samek, and Klaus-Robert M \.

Pathwise Explanation of ReLU Neural Networks a ldchen, Alexander Binder, Gr \'e goire Montavon, Wojciech Samek, and Klaus-Robert M \

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:03:52.549087Z

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Observation e9b98aa1-6f20-4b7f-9c84-b94980940334 · outbound

This paper cites A survey on deep learning in medical image analysis.

Pathwise Explanation of ReLU Neural Networks A survey on deep learning in medical image analysis

Reference 12

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Source-reported events for the cited work

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Observation 0807acd5-69c5-4e95-8a39-3afd1e576504 · outbound

This paper cites Explaining nonlinear classification decisions with deep taylor decomposition.

Pathwise Explanation of ReLU Neural Networks Explaining nonlinear classification decisions with deep taylor decomposition

Reference 13

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Source-reported events for the cited work

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Observation 5a9a2dc9-8082-4bab-a746-d236617ea55a · outbound

This paper cites Mordvintsev, Christopher Olah, and Mike Tyka.

Pathwise Explanation of ReLU Neural Networks Mordvintsev, Christopher Olah, and Mike Tyka

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:03:52.505165Z

Source-reported events for the cited work

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Observation bed49908-a3c0-40fc-8b58-f7f55bb619e0 · outbound

This paper cites RISE: randomized input sampling for explanation of black-box models.

Pathwise Explanation of ReLU Neural Networks RISE: randomized input sampling for explanation of black-box models

Reference 15

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Observation 5fe5d778-9e54-4151-9e4b-4adfa699e980 · outbound

This paper cites why should i trust you?.

Pathwise Explanation of ReLU Neural Networks why should i trust you?

Reference 16

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Source-reported events for the cited work

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Observation 90569047-a6cd-4925-a461-efc906795423 · outbound

This paper cites Imagenet large scale visual recognition challenge.

Pathwise Explanation of ReLU Neural Networks Imagenet large scale visual recognition challenge

Reference 17

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Source-reported events for the cited work

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Observation 6f80dc65-9350-418e-8239-8e92c9fbf5f6 · outbound

This paper cites Locally Linear Attributes of ReLU Neural Networks.

Pathwise Explanation of ReLU Neural Networks Locally Linear Attributes of ReLU Neural Networks

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-15T19:03:52.314607Z

Source-reported events for the cited work

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Observation bbbcd9fc-20df-44b3-bdb2-b97792157c19 · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization.

Pathwise Explanation of ReLU Neural Networks Grad-cam: Visual explanations from deep networks via gradient-based localization

Reference 19

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Observation 73217ee5-e8c2-48f5-bb49-1132a01bd4ed · outbound

This paper cites Not Just a Black Box: Learning Important Features Through Propagating Activation Differences.

Pathwise Explanation of ReLU Neural Networks Not Just a Black Box: Learning Important Features Through Propagating Activation Differences

Reference 20

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Observation fe8b7708-fc13-4122-9d51-e0bf18181c4a · outbound

This paper cites Very deep convolutional networks for large-scale image recognition.

Pathwise Explanation of ReLU Neural Networks Very deep convolutional networks for large-scale image recognition

Reference 21

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Observation 0ad3d107-f65b-4b53-96d9-d8274ba907c0 · outbound

This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Pathwise Explanation of ReLU Neural Networks Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 22

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Observation 941becf8-0054-4309-bbf3-8eb71eb17546 · outbound

This paper cites Striving for Simplicity: The All Convolutional Net.

Pathwise Explanation of ReLU Neural Networks Striving for Simplicity: The All Convolutional Net

Reference 23

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Observation c8f90062-e08a-4b0d-bc56-3966ec83f354 · outbound

This paper cites Unwrapping The Black Box of Deep ReLU Networks: Interpretability, Diagnostics, and Simplification.

Pathwise Explanation of ReLU Neural Networks Unwrapping The Black Box of Deep ReLU Networks: Interpretability, Diagnostics, and Simplification

Reference 24

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Observation 4e183d51-b63a-44af-bdf2-34dd1f646570 · outbound

This paper cites Axiomatic attribution for deep networks.

Pathwise Explanation of ReLU Neural Networks Axiomatic attribution for deep networks

Reference 25

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Observation 460b0252-2832-4757-889c-baf4289b5daa · outbound

This paper cites Unwrapping All ReLU Networks.

Pathwise Explanation of ReLU Neural Networks Unwrapping All ReLU Networks

Reference 26

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Observation 44ef0517-ac66-413c-915a-0090a6ee9b57 · outbound

This paper cites Attribution in scale and space.

Pathwise Explanation of ReLU Neural Networks Attribution in scale and space

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:03:52.399745Z

Source-reported events for the cited work

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Observation 0237a08c-c1e0-4858-a64d-32263efc08d0 · outbound

This paper cites A survey of autonomous driving: Common practices and emerging technologies.

Pathwise Explanation of ReLU Neural Networks A survey of autonomous driving: Common practices and emerging technologies

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:03:52.384637Z

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Observation acff9542-fc66-4ea7-8ac7-ec4b6928cd4c · outbound

This paper cites Visualizing and understanding convolutional networks.

Pathwise Explanation of ReLU Neural Networks Visualizing and understanding convolutional networks

Reference 29

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Observation b5022c60-7e23-48f7-b4d9-d9193915128a · outbound

This paper cites Learning deep features for discriminative localization.

Pathwise Explanation of ReLU Neural Networks Learning deep features for discriminative localization

Reference 30

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Observation b6d80393-e628-4ecf-9a05-2f125d62e61b · outbound

This paper cites Traffic-sign detection and classification in the wild.

Pathwise Explanation of ReLU Neural Networks Traffic-sign detection and classification in the wild

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:03:52.343681Z

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Pith citing papers

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