Paper Citation Record · LEDGER

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks

As of 19 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2605.15328.

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

pith.paper-citation-record.v1
2605.15328 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-19T16:06:05.508610Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T13:37:35.691503Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-03T04:47:38.403600Z

Reference resolution

31 of 31 outbound references displayed

verified exact17
verified fuzzy4
unresolved7
parse uncertain0
malformed identifier1
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2828bfe8-5e1d-45b9-a15e-4ac8430e163b · outbound

This paper cites an unresolved cited work.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Unresolved cited work

Reference 1

Resolution: verified exact; doi, observed 2026-05-19T16:07:40.273810Z

Source-reported events for the cited work

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Observation 55125737-c1dd-4eb5-a970-f67a709807e9 · outbound

This paper cites an unresolved cited work.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-05-19T16:13:08.877361Z

Source-reported events for the cited work

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Observation eb52e774-95d6-41bd-9a6e-f7ea14e557f2 · outbound

This paper cites Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

Reference 3

Resolution: verified exact; doi, observed 2026-05-19T16:07:40.269354Z

Source-reported events for the cited work

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Observation da74cd9d-d788-467c-ae5d-a467eed85bec · outbound

This paper cites Mechanistic Interpretability for AI Safety -- A Review.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Mechanistic Interpretability for AI Safety -- A Review

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:22:15.575714Z

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Observation 9250c159-534e-44b3-8583-1a5387d17a80 · outbound

This paper cites an unresolved cited work.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-05-19T16:13:08.879109Z

Source-reported events for the cited work

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Observation bf542dfa-1a17-4382-bae6-a426efae7264 · outbound

This paper cites Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-19T16:07:41.072408Z

Source-reported events for the cited work

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Observation 7704bfa7-14fd-4c5a-bab5-e619f4520a25 · outbound

This paper cites an unresolved cited work.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Unresolved cited work

Reference 7

Resolution: verified exact; doi, observed 2026-05-19T16:07:40.277238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 34d73e4c-8c08-4191-b8f1-2d7c0b53ce2d · outbound

This paper cites Balasubramanian.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Balasubramanian

Reference 8

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Source-reported events for the cited work

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Observation 77ef80de-eaba-4bbf-b69e-6ff97f245dda · outbound

This paper cites an unresolved cited work.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-05-19T16:13:08.873829Z

Source-reported events for the cited work

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Observation 9eaf3925-d6a3-4768-b8f7-b96761bbf5e2 · outbound

This paper cites Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:07:41.062745Z

Source-reported events for the cited work

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Observation e4a65579-fb7a-4874-a8b3-a24a5812bab6 · outbound

This paper cites Fong and Andrea Vedaldi.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Fong and Andrea Vedaldi

Reference 11

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Source-reported events for the cited work

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Observation 540a2dd8-b6c1-4a46-b7d8-b72425f6549b · outbound

This paper cites Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:07:41.081855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ad030959-148e-476c-bc81-e6214701abc0 · outbound

This paper cites Metrics for saliency map evaluation of deep learning explanation methods.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Metrics for saliency map evaluation of deep learning explanation methods

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:07:41.076840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b95f1ace-1392-4676-84b8-5d502f17da74 · outbound

This paper cites Evaluations and Methods for Explanation through Robustness Analysis.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Evaluations and Methods for Explanation through Robustness Analysis

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:07:41.049258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 48ccedf7-3535-430f-89bd-4a4316923c9e · outbound

This paper cites Causal Machine Learning: A Survey and Open Problems.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Causal Machine Learning: A Survey and Open Problems

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-28T02:04:06.087256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8b9dc27e-790c-4b9f-9652-c40f9795efba · outbound

This paper cites Kotsiantis.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Kotsiantis

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T16:13:08.870221Z

Source-reported events for the cited work

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Observation 429a89cf-863a-4909-b80b-9ac0c962aed5 · outbound

This paper cites Lundberg and Su-In Lee.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Lundberg and Su-In Lee

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T16:13:08.875648Z

Source-reported events for the cited work

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Observation 9481266b-916f-460d-b7d3-f79f3148eebc · outbound

This paper cites an unresolved cited work.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Unresolved cited work

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:07:40.264794Z

Source-reported events for the cited work

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Observation a9b3fd49-1d69-4f04-bd2c-09af88c9dcc4 · outbound

This paper cites Distill , year =.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Distill , year =

Reference 19

Resolution: verified exact; doi, observed 2026-05-19T16:07:40.254746Z

Source-reported events for the cited work

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Observation 4ec9f35e-90a8-4845-b29e-50a556545917 · outbound

This paper cites RISE: Randomized Input Sampling for Explanation of Black-box Models.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks RISE: Randomized Input Sampling for Explanation of Black-box Models

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-19T16:07:41.087029Z

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Observation e376ebf9-8bb2-44da-b428-ca37cf28fbe8 · outbound

This paper cites Why Should I Trust You?.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Why Should I Trust You?

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:07:40.291853Z

Source-reported events for the cited work

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Observation 3d49be27-b53b-4112-84ac-66a4ac9bd73d · outbound

This paper cites Reinforcement Learning-based Decentralized Optimal Control for Large- Scale Multi-agent System by Using Neural Networks and Discrete-time Mean Field Games.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Reinforcement Learning-based Decentralized Optimal Control for Large- Scale Multi-agent System by Using Neural Networks and Discrete-time Mean Field Games

Reference 22

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Observation bc5b1ed4-2ba3-4f51-a081-39051396e73d · outbound

This paper cites an unresolved cited work.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Unresolved cited work

Reference 23

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Observation 812b37a7-0456-4743-9041-fc2cc4d7b7f4 · outbound

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

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-19T16:07:41.093296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 903c7cdb-710f-4665-8e4b-f54efe9d9b66 · outbound

This paper cites Visualizing the Impact of Feature Attribution Baselines.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Visualizing the Impact of Feature Attribution Baselines

Reference 25

Resolution: verified exact; doi, observed 2026-05-19T16:07:40.281689Z

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Observation 9d74830c-352c-431f-a036-c0a5118ee7fd · outbound

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From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Unresolved cited work

Reference 26

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Observation f70f20a1-632d-41d5-be9a-7ef1a0629098 · outbound

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

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Gomez, Łukasz Kaiser, and Illia Polosukhin

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T16:13:08.882587Z

Source-reported events for the cited work

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Observation 96f01e81-4f98-47f5-844e-2f77f6a85c59 · outbound

This paper cites an unresolved cited work.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-05-19T16:13:08.886669Z

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Observation fb9c287b-a587-4b7b-ae31-99d251a8faeb · outbound

This paper cites an unresolved cited work.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Unresolved cited work

Reference 29

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Observation e4f6ab7f-af2b-483e-a19c-947dd4fef112 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-05-19T16:07:41.102367Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f512d05c-7326-4c3b-a525-c3db59bac4c8 · outbound

This paper cites Zeiler and Rob Fergus.

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Zeiler and Rob Fergus

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T16:13:08.890768Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation fc4c033d-7697-46c8-9a77-d811e5110603 · inbound

XtrAIn: Training-Guided Occlusion for Feature Attribution cites this paper.

XtrAIn: Training-Guided Occlusion for Feature Attribution From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-07-03T04:47:38.404787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.