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Paper Citation Record · LEDGER

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation

As of 12 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2412.09311.

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

pith.paper-citation-record.v1
2412.09311 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:11:11.340375Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

58 of 58 outbound references displayed

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  • verified fuzzy5
  • unresolved48
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 71ee218a-4120-4f67-87aa-828598509de0 · outbound

This paper cites an unresolved cited work.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 1

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This paper cites an unresolved cited work.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 2

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Observation e20e6748-05e7-4781-bf3e-9be4100e5a41 · outbound

This paper cites an unresolved cited work.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 3

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Reference 4

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 5

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This paper cites an unresolved cited work.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 6

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 7

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Observation 65d7f5c5-7f33-4381-a5c1-3ba0a0914e42 · outbound

This paper cites Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI

Reference 8

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Observation a1fdf489-37f6-47a9-bd07-d87e12185c80 · outbound

This paper cites One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques

Reference 9

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 10

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This paper cites Evaluating and Aggregating Feature-based Model Explanations.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Evaluating and Aggregating Feature-based Model Explanations

Reference 11

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 12

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 13

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 14

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 15

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Framework for Evaluating Faithfulness of Local Explanations

Reference 16

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Reference 17

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 18

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 19

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Use HiResCAM instead of Grad-CAM for faithful explanations of convolutional neural networks

Reference 20

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Everingham, L

Reference 21

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Reference 22

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks

Reference 33

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Reference 34

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 35

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 36

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This paper cites Why Should I Trust You?.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Why Should I Trust You?

Reference 37

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Observation ffc3c2da-ff46-4488-923b-b2539bd8b31a · outbound

This paper cites IROF: a low resource evaluation metric for explanation methods.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation IROF: a low resource evaluation metric for explanation methods

Reference 38

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Observation 189156f5-2bfe-4bde-bec5-3b44f2470080 · outbound

This paper cites In Proceedings of the 38th International Conference on Machine Learning, ICML 2021 (Proceedings of Machine Learning Research, Vol.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation In Proceedings of the 38th International Conference on Machine Learning, ICML 2021 (Proceedings of Machine Learning Research, Vol

Reference 39

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Observation 94fae239-db31-42e2-a7b9-0145d656a671 · outbound

This paper cites Berg, and Li Fei-Fei.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Berg, and Li Fei-Fei

Reference 40

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Observation 83346cff-845f-492c-951b-3d6713db3394 · outbound

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 41

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Observation 5a2194d6-757c-44d0-92e9-84c80bd216e5 · outbound

This paper cites A Consistent and Efficient Evaluation Strategy for Attribution Methods.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation A Consistent and Efficient Evaluation Strategy for Attribution Methods

Reference 42

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Observation fb28e182-454d-4c26-86c1-c86c27d4aceb · outbound

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

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Not Just a Black Box: Learning Important Features Through Propagating Activation Differences

Reference 43

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Observation 51f710aa-9f21-47bf-9127-d0b20f5a42a9 · outbound

This paper cites an unresolved cited work.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 44

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This paper cites Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra

Reference 45

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Reference 47

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Observation 3a6817d2-9814-4e7c-9ac0-2df82a41d405 · outbound

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 48

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Observation c12c320e-1bbe-4fe4-b3c5-fec101a41aca · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 49

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Observation 8ada45c2-5d0b-4863-8c8c-53844f66917f · outbound

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

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 50

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Observation 904efc46-725a-42b8-ad38-f319a340ac33 · outbound

This paper cites Courville, Ruslan Salakhutdinov, Richard S.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Courville, Ruslan Salakhutdinov, Richard S

Reference 51

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Observation 80fcca82-ae63-41ba-9bbb-bc6ea805e691 · outbound

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Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 52

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Observation 3224ff3d-8a2d-464b-a74c-48dc8344bd95 · outbound

This paper cites Zeiler and Rob Fergus.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Zeiler and Rob Fergus

Reference 53

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Observation 91217245-c25b-474f-a307-cc86272a3e15 · outbound

This paper cites an unresolved cited work.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 54

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation d64674ab-beb3-4ff4-af59-d5dcd74f840e · outbound

This paper cites an unresolved cited work.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Unresolved cited work

Reference 55

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Observation 453b7ed7-c322-4b9a-8dda-3e1dedd88d40 · outbound

This paper cites PLOS ONE 10, 7 (jul 2015), e0130140.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation PLOS ONE 10, 7 (jul 2015), e0130140

Reference 2015

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Observation c7e2434a-8f23-469b-bc48-5c7eed29fd3e · outbound

This paper cites Nature 529, 7587 (Jan.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Nature 529, 7587 (Jan

Reference 2016

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Observation 2900498d-7a96-4ba0-b6ea-164c734fda6a · outbound

This paper cites International Journal of Computer Vision 128, 2 (oct 2019), 336–359.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation International Journal of Computer Vision 128, 2 (oct 2019), 336–359

Reference 2019

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Observation 427be864-3ebf-4818-a14f-aa9ff705bdaf · outbound

This paper cites https://openreview.net/forum?id=XPZIaotutsD.

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation https://openreview.net/forum?id=XPZIaotutsD

Reference 2021

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raw_fallback, observed 2026-08-11T17:11:11.949227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Pith citing papers

No inbound Pith citation observations are available.