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Paper Citation Record · LEDGER

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks

As of 16 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 4 inbound Pith citation observations for arXiv:2508.21715.

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

pith.paper-citation-record.v1
2508.21715 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:05:55.875820Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T06:44:52.762530Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T06:45:29.222719Z

Reference resolution

27 of 27 outbound references displayed

  • verified exact1
  • verified fuzzy11
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1722ddac-f982-44ae-9f5a-a82ee4897511 · outbound

This paper cites These information metrics provide non-invasive profiling of feature transformations across the network, enabling early detection of deviations in representation quality.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks These information metrics provide non-invasive profiling of feature transformations across the network, enabling early detection of deviations in representation quality

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-05T14:05:56.628774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 4be48d79-5515-47af-ba06-ab7905f69fad · outbound

This paper cites an unresolved cited work.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation b65cc29f-a1c2-4450-9b13-684b12352ecb · outbound

This paper cites an unresolved cited work.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Unresolved cited work

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 91450e45-6f20-49da-9557-d81e72891e9d · outbound

This paper cites an unresolved cited work.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Unresolved cited work

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 60601850-b69b-431b-8393-4c0159771ea5 · outbound

This paper cites W., et al.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks W., et al

Reference 5

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raw_fallback, observed 2026-08-05T14:05:56.530877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 62da98c2-2b24-43a5-a49c-3bb4b5c2005d · outbound

This paper cites an unresolved cited work.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 4274f403-aea8-445b-bf60-1fe5526c43a3 · outbound

This paper cites an unresolved cited work.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Unresolved cited work

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 0a157b38-7835-4ef7-8d22-ff5350fbc66c · outbound

This paper cites an unresolved cited work.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Unresolved cited work

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation cadfc73c-087a-40c3-8515-260f97acce28 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 9

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no resolver link, observed 2026-08-05T14:05:55.746371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:05:55.746371Z digest=sha256:1109f1ad5c51935439810a02ab993bd7f1833eb1c6b621886c6b26cdcc3ab29c

Observation 4cc35895-37c4-4fb8-ab4f-d210c126f76a · outbound

This paper cites Unlike existing methods, our framework operates in parallel to the original network, requiring no architectural modifications, retraining, or multiple forward passes.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Unlike existing methods, our framework operates in parallel to the original network, requiring no architectural modifications, retraining, or multiple forward passes

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-05T14:05:56.654999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 61a3eee3-928a-4b1d-b5c4-30b2d08e985f · outbound

This paper cites Energy-based out-of-distribution detection.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Energy-based out-of-distribution detection

Reference 11

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raw_fallback, observed 2026-08-05T14:05:56.412683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T14:05:55.758333Z digest=sha256:2d1b7c0df6458d37540820cc5bbb50f4525444167a356f226f1eb4a1b54ff1ed

Observation ee08a3df-6abe-4eb8-87f1-fa8ba0388b1c · outbound

This paper cites Opening the Black Box of Deep Neural Networks via Information.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Opening the Black Box of Deep Neural Networks via Information

Reference 12

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no resolver link, observed 2026-08-05T14:05:55.763734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 68f7cc9c-8396-4bc9-bb30-3381b23cf9fa · outbound

This paper cites Detecting Adversarial Samples from Artifacts.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Detecting Adversarial Samples from Artifacts

Reference 13

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no resolver link, observed 2026-08-05T14:05:55.787098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:05:55.787098Z digest=sha256:55e43aaa828fce37f93532f55c3a87090ddfb6aaecbc4d10d64c0aa7b39a93c9

Observation 056ddc27-0622-40cb-96ac-b4d62641e63b · outbound

This paper cites Generalized Out-of-Distribution Detection: A Survey.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Generalized Out-of-Distribution Detection: A Survey

Reference 15

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no resolver link, observed 2026-08-05T14:05:55.802454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:05:55.802454Z digest=sha256:97783941730baa9b7d9f15c104e88b1bfe8385e68f843d67b8686878618abbe3

Observation e795a04d-41c5-4d69-bd33-f14d0cc1b95a · outbound

This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 16

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no resolver link, observed 2026-08-05T14:05:55.807734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:05:55.807734Z digest=sha256:4c895775902126d7ec04ae5890db2981f8b5c1416cc827f7cb2e24cd612acf28

Observation 8cfda750-e0b7-4a55-af90-21b2cdbf771d · outbound

This paper cites Evidential deep learning to quantify classification uncertainty.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Evidential deep learning to quantify classification uncertainty

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-05T14:05:56.345292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 11155eb1-82b9-4a7c-9e88-4f23486ab96e · outbound

This paper cites Predictive uncertainty estimation via prior networks.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Predictive uncertainty estimation via prior networks

Reference 18

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raw_fallback, observed 2026-08-05T14:05:56.319102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T14:05:55.821632Z digest=sha256:cdc4b5e26e638d398c87d02fececf40441f88f021dc4fd619118cca4387c8864

Observation 71457af4-c7fa-4787-8d4f-539240e90997 · outbound

This paper cites Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks

Reference 21

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no resolver link, observed 2026-08-05T14:05:55.826417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:05:55.826417Z digest=sha256:0be8356b91f895975559ac3f6db38c2847ee54b12323586e674077111e6ecc9b

Observation fec3b609-788e-4397-b85a-679aa08941f4 · outbound

This paper cites Deep learning and the information bottleneck principle.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Deep learning and the information bottleneck principle

Reference 22

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raw_fallback, observed 2026-08-05T14:05:56.293804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T14:05:55.834494Z digest=sha256:021d9b855f84836be192a00d0f8539a27c409424ed59cb96c3d714b71e512ad5

Observation a2d42d13-cc94-42cf-936c-b506dd2f3ce4 · outbound

This paper cites Estimating Information Flow in Deep Neural Networks.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Estimating Information Flow in Deep Neural Networks

Reference 23

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verified exact
local_arxiv, observed 2026-08-05T14:05:55.947894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T14:05:55.847559Z digest=sha256:3ade0177dccf638adcaaa8a8a199f55441efaee01db3f9f3739bc9b8adfe86f3

Observation d805557d-781c-46a5-96d3-c86af5eb8d22 · outbound

This paper cites Scalable mutual information estimation using dependence graphs.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Scalable mutual information estimation using dependence graphs

Reference 24

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raw_fallback, observed 2026-08-05T14:05:56.267434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5c3070ac-41a7-4a8b-83eb-81264c74e39b · outbound

This paper cites The information bottleneck problem and its applications in machine learning.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks The information bottleneck problem and its applications in machine learning

Reference 25

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raw_fallback, observed 2026-08-05T14:05:56.234839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 566c488d-37f4-426f-9bae-c5ab53c4f225 · outbound

This paper cites an unresolved cited work.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Unresolved cited work

Reference 26

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation c5517b7e-19a9-488b-b6a1-fab08243d384 · outbound

This paper cites (2025, May).

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks (2025, May)

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-05T14:05:56.185347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 96eec4a1-a8c2-46f8-9555-c5fcf3768e56 · outbound

This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 2016

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no resolver link, observed 2026-08-05T14:05:55.779631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:05:55.779631Z digest=sha256:437013cba3719e2be964c0843268e0cb2b3a06b015d9155f830f9015d78514bc

Observation 6108d552-3566-47e4-9995-033458177d69 · outbound

This paper cites On Detecting Adversarial Perturbations.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks On Detecting Adversarial Perturbations

Reference 2017

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no resolver link, observed 2026-08-05T14:05:55.794047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:05:55.794047Z digest=sha256:e345799a9f5115860bf913b8a5c463d3df3815172e1ac6a0146cfe4b40cff17b

Observation 20710f82-466a-4905-b69b-ed363e254610 · outbound

This paper cites Journal of Statistical Mechanics: Theory and Experiment, 2019(12), p.124020.

Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks Journal of Statistical Mechanics: Theory and Experiment, 2019(12), p.124020

Reference 2019

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raw_fallback, observed 2026-08-05T14:05:56.382357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Pith citing papers

Observation 1cc58c00-990c-42ca-b6f5-38f6989215a6 · inbound

The Informational Cost of Agency: A Bounded Measure of Interaction Efficiency for Deployed Reinforcement Learning cites this paper.

The Informational Cost of Agency: A Bounded Measure of Interaction Efficiency for Deployed Reinforcement Learning Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks

Reference 1

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verified exact
arxiv_id, observed 2026-05-15T17:40:11.801097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-15T17:37:03.704563Z digest=sha256:4a932237e1149772e9a39aa7cca1a762c58f4988f81b0efb28ffb0a5a460975c

Observation 5f268737-855a-45fe-9122-7353f991a054 · inbound

The Informational Cost of Agency: A Bounded Measure of Interaction Efficiency for Deployed Reinforcement Learning cites this paper.

The Informational Cost of Agency: A Bounded Measure of Interaction Efficiency for Deployed Reinforcement Learning Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks

Reference 1

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verified exact
arxiv_id, observed 2026-05-21T11:45:03.189714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-21T11:44:30.880602Z digest=sha256:fc54e6bc5e3c1a10f6fffb4431fe157a090d2742ee6d923ec58d45dde39ad26d

Observation 07e2bd14-3815-4486-a85a-e87f80d44f38 · inbound

A Classifier-Agnostic Zero-Shot Adversarial Attack Detection via CLIP cites this paper.

A Classifier-Agnostic Zero-Shot Adversarial Attack Detection via CLIP Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks

Reference 29

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metadata mismatch
arxiv_id, observed 2026-06-30T06:44:19.667178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-30T06:35:43.534963Z digest=sha256:0639ecdfd31593a89f2f03615578ce68331ca787455fdb109019c8014536beae

Observation 0b5b5ebb-63bd-478d-868f-f8fb3796e318 · inbound

A Classifier-Agnostic Zero-Shot Adversarial Attack Detection via CLIP cites this paper.

A Classifier-Agnostic Zero-Shot Adversarial Attack Detection via CLIP Entropy-Based Non-Invasive Reliability Monitoring of Convolutional Neural Networks

Reference 29

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metadata mismatch
arxiv_id, observed 2026-07-01T06:45:29.224502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-07-01T06:44:52.762530Z digest=sha256:228c45051a1f6cb68f25a7d5b31a0c8b2c317e67478ab7104ec30b73a4519c79