Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-19T16:06:05.508610Z
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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-27T13:37:35.691503Z
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
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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 2026-08-18T06:34:40.430872+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
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-19T16:07:40.259715Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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 2026-08-18T06:34:40.430872+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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9d74830c-352c-431f-a036-c0a5118ee7fd · outbound
This paper cites an unresolved cited work.
From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks Unresolved cited work
Reference 26
- Resolution
- unresolved
- raw_fallback, observed 2026-05-19T16:13:08.880826Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+00:00.