Paper Citation Record · LEDGER

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing

As of 22 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 2 inbound Pith citation observations for arXiv:2505.04318.

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

pith.paper-citation-record.v1
2505.04318 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:37:01.879725Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:35:29.314976Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T09:06:49.157464Z

Reference resolution

19 of 19 outbound references displayed

verified exact1
verified fuzzy9
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ff265bd5-285c-438e-ac03-158815c22aba · outbound

This paper cites Detecting concept drift with neural network model uncertainty, 2022.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Detecting concept drift with neural network model uncertainty, 2022

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:37:02.368325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c20cbbac-03c8-471d-a440-80944bbe66e6 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing The mnist database of handwritten digit images for machine learning research

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T23:37:01.808583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1342712-ed51-42bb-be82-6ed827e8be69 · outbound

This paper cites Learning in nonstationary environments: A survey.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Learning in nonstationary environments: A survey

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T23:37:01.812720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01f14f15-3bf6-4f97-ae28-b92146725ed9 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T23:37:01.817273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df684e0a-8bc5-4124-81be-cb511fc73627 · outbound

This paper cites an unresolved cited work.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Unresolved cited work

Reference 5

Resolution: verified exact; raw_fallback, observed 2026-08-15T23:37:02.132875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation da9df369-e449-4a68-9de0-0f700273125e · outbound

This paper cites an unresolved cited work.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:37:02.344830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3ba6a321-96ae-47b1-91ae-e755e6b8a524 · outbound

This paper cites Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:37:02.328547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 261ebc8e-97d6-4e33-9a2c-70c446d39e52 · outbound

This paper cites Vision transformers in pytorch for mnist handwritten.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Vision transformers in pytorch for mnist handwritten

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:37:02.315521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 21573010-5496-462d-9420-e663e87fb36d · outbound

This paper cites An overview on concept drift learning.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing An overview on concept drift learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:37:02.302430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3d40f577-cc5a-49de-a14e-e7ec760937d4 · outbound

This paper cites LeCun, B.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing LeCun, B

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T23:37:01.842381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b866d9fe-2aa1-43ed-af78-730f10230e21 · outbound

This paper cites Probability, Statistics, and Random Processes for Electrical Engineering.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Probability, Statistics, and Random Processes for Electrical Engineering

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:37:02.289416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 33aeaa65-3abf-487e-8a61-77f0a82f438f · outbound

This paper cites Too big to fail: Large samples and the p-value problem.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Too big to fail: Large samples and the p-value problem

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T23:37:01.850572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7033bc2-3937-4101-8d01-6840c8f02805 · outbound

This paper cites Learning under concept drift: A review.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Learning under concept drift: A review

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T23:37:01.854877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dfc3653-725a-42d8-8871-4d41b7722892 · outbound

This paper cites PyTorch neural networks tutorial.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing PyTorch neural networks tutorial

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:37:02.276576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d6253f16-47f0-4a61-b816-2f5ed6def193 · outbound

This paper cites The perceptron: a probabilistic model for information storage and organization in the brain.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing The perceptron: a probabilistic model for information storage and organization in the brain

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T23:37:01.862810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c218d824-b761-4942-9856-2951fe10565e · outbound

This paper cites Radiations from Radioactive Substances.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Radiations from Radioactive Substances

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:37:02.254763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6533e6ca-3af0-407a-8d2f-43f36ffeb8b0 · outbound

This paper cites Recommendation for the entropy sources used for random bit generation.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Recommendation for the entropy sources used for random bit generation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:37:02.241811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7d64b261-ae1e-4b21-8c44-c8a0af45cbe9 · outbound

This paper cites Alibi Detect: Algorithms for outlier, adversarial and drift detection , July 2023.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Alibi Detect: Algorithms for outlier, adversarial and drift detection , July 2023

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:37:02.228379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a7df4206-96f6-4216-9e34-4aaa1d962442 · outbound

This paper cites Attention is all you need.

Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing Attention is all you need

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T23:37:01.879725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation fe2ac96d-bcbb-4e22-998d-33170440d949 · inbound

EpiEvolve: Self-Evolving Agents for Streaming Pandemic Forecasting under Regime Shifts cites this paper.

EpiEvolve: Self-Evolving Agents for Streaming Pandemic Forecasting under Regime Shifts Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-02T09:06:49.158966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3f3364cb-c42d-40be-a0c4-d1300957d10c · inbound

A Six-Dimensional Taxonomy of Post-Training Adaptation Techniques with Applications in AI Governance cites this paper.

A Six-Dimensional Taxonomy of Post-Training Adaptation Techniques with Applications in AI Governance Detecting Concept Drift in Neural Networks Using Chi-squared Goodness of Fit Testing

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T11:35:29.314976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.