Paper Citation Record · LEDGER

Feature Attribution from First Principles

As of 8 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2505.24729.

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

pith.paper-citation-record.v1
2505.24729 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:26:21.207333Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

42 of 42 outbound references displayed

verified exact1
verified fuzzy37
unresolved4
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f59b222e-f2a1-4729-b37d-7555f0f26f34 · outbound

This paper cites Sanity Checks for Saliency Maps.

Feature Attribution from First Principles Sanity Checks for Saliency Maps

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:30.491584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 416d1291-0dbe-4158-9af8-ff5e8a18e5b3 · outbound

This paper cites OpenXAI: Towards a Transparent Evaluation of Model Explanations.

Feature Attribution from First Principles OpenXAI: Towards a Transparent Evaluation of Model Explanations

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:30.163685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 00deb67e-d5b4-4144-9fd8-4e35cd06b210 · outbound

This paper cites Functions of bounded variation, signed measures, and a general Koksma-Hlawka inequality.

Feature Attribution from First Principles Functions of bounded variation, signed measures, and a general Koksma-Hlawka inequality

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:29.890513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8d3c4ef7-1086-4644-8419-53006824dba0 · outbound

This paper cites Towards better understanding of gradient-based attribution methods for Deep Neural Networks.

Feature Attribution from First Principles Towards better understanding of gradient-based attribution methods for Deep Neural Networks

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:29.615840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1390bfc0-2707-4ba8-98fb-9665676b9272 · outbound

This paper cites On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation.

Feature Attribution from First Principles On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:29.491698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fcf3250c-d34d-4e9b-a4cc-5b4b629b76e9 · outbound

This paper cites Are Artificial Neural Networks Black Boxes? IEEE Transactions on Neural Networks, 1997.

Feature Attribution from First Principles Are Artificial Neural Networks Black Boxes? IEEE Transactions on Neural Networks, 1997

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:29.349637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0774258e-0cc4-4553-bd6d-5d32c24e3ad6 · outbound

This paper cites How to safely discard features based on aggregate SHAP values.

Feature Attribution from First Principles How to safely discard features based on aggregate SHAP values

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:26:21.604562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7737d782-0e1b-4260-bd6a-1802a696a18f · outbound

This paper cites Impossibility Theorems for Feature Attribution.

Feature Attribution from First Principles Impossibility Theorems for Feature Attribution

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:29.108236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e7be83fc-042d-4d2d-bea7-92297a92e6b5 · outbound

This paper cites Functions of bounded variation in one and multiple dimensions.

Feature Attribution from First Principles Functions of bounded variation in one and multiple dimensions

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:28.947194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9554821e-9e62-41c4-8f61-e6d9c2cec2ab · outbound

This paper cites A Theory of Interpretable Approximations.

Feature Attribution from First Principles A Theory of Interpretable Approximations

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:28.708396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d43e4cf0-6692-4e58-b1ff-3daa721cc4c4 · outbound

This paper cites Introduction to Calculus and Analysis (volume II).

Feature Attribution from First Principles Introduction to Calculus and Analysis (volume II)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:28.536981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c791fe09-01e9-47d0-bc44-3f0e97db9fda · outbound

This paper cites Explaining by Removing: A Unified Framework for Model Explanation.

Feature Attribution from First Principles Explaining by Removing: A Unified Framework for Model Explanation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:28.205537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bf68396a-89d1-433d-a168-2fecc20932f5 · outbound

This paper cites Attribution-based Explanations that Provide Recourse Cannot be Robust.

Feature Attribution from First Principles Attribution-based Explanations that Provide Recourse Cannot be Robust

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:27.904427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bc9ab381-8a61-487d-b5cb-b4204e4dc57c · outbound

This paper cites Real analysis: modern techniques and their applications.

Feature Attribution from First Principles Real analysis: modern techniques and their applications

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f797355-76a0-44d2-89c4-4ffc6f8ab9e8 · outbound

This paper cites Greedy Function Approximation: A Gradient Boosting Machine.

Feature Attribution from First Principles Greedy Function Approximation: A Gradient Boosting Machine

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:27.526271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e315435d-d193-474b-9ae7-eeeb4c262b54 · outbound

This paper cites What does LIME really see in images? In International Conference on Machine Learning.

Feature Attribution from First Principles What does LIME really see in images? In International Conference on Machine Learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:27.229416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b55d81d8-0064-44c3-9a61-b5bfed6d3165 · outbound

This paper cites Interpretation of Neural Networks is Fragile.

Feature Attribution from First Principles Interpretation of Neural Networks is Fragile

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:26.937562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a0d5933f-bdec-484d-86ff-23e7a06a74f8 · outbound

This paper cites New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound.

Feature Attribution from First Principles New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:26.608188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1acce2d3-a822-42d3-8ea3-19cc3616c56f · outbound

This paper cites Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations.

Feature Attribution from First Principles Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:26.174674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cfc24d80-9d09-4407-a1b8-d47df7e10c0b · outbound

This paper cites Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond.

Feature Attribution from First Principles Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:25.893757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5d84d3b6-fc1f-4bcc-9e81-614d8e7cb15a · outbound

This paper cites Fooling Neural Network Interpretations via Adversarial Model Manipulation.

Feature Attribution from First Principles Fooling Neural Network Interpretations via Adversarial Model Manipulation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:25.580656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a056e63a-24f4-4186-8a6a-423dab28175e · outbound

This paper cites Fast Axiomatic Attribution for Neural Networks.

Feature Attribution from First Principles Fast Axiomatic Attribution for Neural Networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:25.244364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1f03370d-7171-401c-b2f9-34461b5e2505 · outbound

This paper cites an unresolved cited work.

Feature Attribution from First Principles Unresolved cited work

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2c9eb3a5-d88b-468e-a4f2-37db8154da4e · outbound

This paper cites A Benchmark for Interpretability Methods in Deep Neural Networks.

Feature Attribution from First Principles A Benchmark for Interpretability Methods in Deep Neural Networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:25.076977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3037aa5e-ba72-4277-b3da-03c3ab2a3534 · outbound

This paper cites SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries.

Feature Attribution from First Principles SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:24.922135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 218acde2-08d9-4d67-a6f0-96013244aadc · outbound

This paper cites Concrete Representation of Abstract (M)-Spaces (A characterization of the Space of Continuous Functions).

Feature Attribution from First Principles Concrete Representation of Abstract (M)-Spaces (A characterization of the Space of Continuous Functions)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:24.694766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7d0358ef-306b-4b62-895d-637c7a15b023 · outbound

This paper cites The (Un)reliability of saliency methods.

Feature Attribution from First Principles The (Un)reliability of saliency methods

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:24.554702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 73351246-30e9-4e91-9c78-157dff0fd74e · outbound

This paper cites Disentangling Interactions and Dependencies in Feature Attribution.

Feature Attribution from First Principles Disentangling Interactions and Dependencies in Feature Attribution

Reference 28

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Source-reported events for the cited work

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Observation 2aa5d55d-be7f-420b-882e-1fde9c94a6b4 · outbound

This paper cites Attention Meets Post-hoc Inter- pretability: A Mathematical Perspective.

Feature Attribution from First Principles Attention Meets Post-hoc Inter- pretability: A Mathematical Perspective

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:24.430186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3e1ab81f-35a7-40b3-af0b-a5dc8025b7c4 · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

Feature Attribution from First Principles A Unified Approach to Interpreting Model Predictions

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:24.278975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2c63c8c7-83a4-44f1-b5e8-750c55a6f7f6 · outbound

This paper cites Continuous Linear Representations.

Feature Attribution from First Principles Continuous Linear Representations

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:24.139277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b104630e-18f8-433d-abf4-f5bca213ecae · outbound

This paper cites Tangent Sets in the Space of Measures: With Applications to Variational Analysis.

Feature Attribution from First Principles Tangent Sets in the Space of Measures: With Applications to Variational Analysis

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:24.022095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e1984eb1-f3f2-4022-84fa-c64ece526c5a · outbound

This paper cites Steepest descent algorithms in a space of measures.Statistics and Computing, 2002.

Feature Attribution from First Principles Steepest descent algorithms in a space of measures.Statistics and Computing, 2002

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:23.873745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ae4bf3c0-00de-4ff7-93c0-25eb62be7974 · outbound

This paper cites Multidimensional Variation for Quasi-Monte Carlo.

Feature Attribution from First Principles Multidimensional Variation for Quasi-Monte Carlo

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:23.737256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 94659e82-1d55-4983-838b-e0ae20576d73 · outbound

This paper cites Mathematical theory of deep learning.

Feature Attribution from First Principles Mathematical theory of deep learning

Reference 35

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Source-reported events for the cited work

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Observation 0094b8bd-9fd1-4ed1-8111-b924b38cf976 · outbound

This paper cites Why Should I Trust You?.

Feature Attribution from First Principles Why Should I Trust You?

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:23.462336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7a316bf8-6eb0-40cc-9bc2-cc54bfa0d0eb · outbound

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

Feature Attribution from First Principles A Consistent and Efficient Evaluation Strategy for Attribution Methods

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:23.183540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3a593242-087a-4c2d-8150-af8877a6cc65 · outbound

This paper cites Principles of Mathematical Analysis.

Feature Attribution from First Principles Principles of Mathematical Analysis

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:22.914199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d7aa6055-e003-4f85-89fa-3b22c19ccb62 · outbound

This paper cites Grad-CAM: Visual Explanations from Deep Networks via Gradient- based Localization.

Feature Attribution from First Principles Grad-CAM: Visual Explanations from Deep Networks via Gradient- based Localization

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:22.675227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a7d127ef-ae1e-4be6-b51b-ad2132aece27 · outbound

This paper cites Learning Important Features Through Propagating Activation Differences.

Feature Attribution from First Principles Learning Important Features Through Propagating Activation Differences

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:22.428784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 682c8a9f-5c5d-4538-b7d5-1adf8b63c8a9 · outbound

This paper cites Axiomatic Attribution for Deep Networks.

Feature Attribution from First Principles Axiomatic Attribution for Deep Networks

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:22.123772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d5b70d82-9694-4a28-a304-65b5b3c8b20c · outbound

This paper cites #´ś p‰j ş r0,1s 1 dp1ypą0q ¯ş r0,1s yk dp2ykq if k“ j ,ş r0,1s yk dp1yką0q ş r0,1s 1 dp2yjqś p‰j,k ş r0,1s 1 dp1ypą0q else. (Fubini’s Theorem) “.

Feature Attribution from First Principles #´ś p‰j ş r0,1s 1 dp1ypą0q ¯ş r0,1s yk dp2ykq if k“ j ,ş r0,1s yk dp1yką0q ş r0,1s 1 dp2yjqś p‰j,k ş r0,1s 1 dp1ypą0q else. (Fubini’s Theorem) “

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:21.856867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

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