Paper Citation Record · LEDGER

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective

As of 23 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2507.18996.

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

pith.paper-citation-record.v1
2507.18996 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:08:25.114202Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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 fuzzy29
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a5f8635a-9def-4297-b95e-9c8e98b71b59 · outbound

This paper cites Improving predictive inference under covariate shift by weighting the log-likelihood function.Journal of statistical planning and inference, 90(2):227–244, 2000.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Improving predictive inference under covariate shift by weighting the log-likelihood function.Journal of statistical planning and inference, 90(2):227–244, 2000

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:27.976941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f3944cc4-f53b-408e-a110-e040ee629284 · outbound

This paper cites Covariate shift adaptation by importance weighted cross validation.Journal of Machine Learning Research, 8(5), 2007.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Covariate shift adaptation by importance weighted cross validation.Journal of Machine Learning Research, 8(5), 2007

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:27.938476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5dd5da09-50f2-4dee-bdb3-8530a64a2108 · outbound

This paper cites Causal covariate shift correction using fisher information penalty.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Causal covariate shift correction using fisher information penalty

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:27.798494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1b175552-e71a-4c54-aa09-43622282ac28 · outbound

This paper cites FL Games: A federated learning framework for distribution shifts.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective FL Games: A federated learning framework for distribution shifts

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:23.942050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85d177d7-8d9f-4ba1-ac89-3961f6f70e97 · outbound

This paper cites Oxford university press, 1995.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Oxford university press, 1995

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:27.681238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6299ee10-1246-46a8-9cad-9da3b9d65948 · outbound

This paper cites Fast algorithm selection using learning curves.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Fast algorithm selection using learning curves

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:27.607468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a7d4f761-5dd6-45d5-a5aa-fc7015e91548 · outbound

This paper cites Sample selection bias correction theory.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Sample selection bias correction theory

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:27.494179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 07d0f213-446b-4eca-b231-8048dd89ab3e · outbound

This paper cites The impact of changing populations on classifier performance.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective The impact of changing populations on classifier performance

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:27.417482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e78fe16d-ff8a-4875-943b-57743fed7872 · outbound

This paper cites Classifier technology and the illusion of progress.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Classifier technology and the illusion of progress

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:24.056968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 178ef772-e6ac-44c5-ad1b-8b9e34c0e474 · outbound

This paper cites A framework for monitoring classifiers’ performance: when and why failure occurs?Knowledge and Information Systems, 18(1):83–108, 2009.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective A framework for monitoring classifiers’ performance: when and why failure occurs?Knowledge and Information Systems, 18(1):83–108, 2009

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:27.225304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0aadadc2-23d0-4a55-946a-b267f7580e95 · outbound

This paper cites A unifying view on dataset shift in classification.Pattern recognition, 45(1):521–530, 2012.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective A unifying view on dataset shift in classification.Pattern recognition, 45(1):521–530, 2012

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:27.204136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 499f5b59-bc34-4157-830d-1fb5cb0f96ec · outbound

This paper cites Mit Press, 2009.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Mit Press, 2009

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:27.166252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5a07ff12-2599-4021-acde-4767633766d5 · outbound

This paper cites Eeg-based emotion recognition using deep learning network with principal component based covariate shift adaptation.The Scientific World Journal, 2014, 2014.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Eeg-based emotion recognition using deep learning network with principal component based covariate shift adaptation.The Scientific World Journal, 2014, 2014

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:27.046470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3da5b2e2-11f4-4d0d-86a0-131d00dfcac7 · outbound

This paper cites A weighted support vector machine for data classification.International Journal of Pattern Recognition and Artificial Intelligence, 21(05):961–976, 2007.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective A weighted support vector machine for data classification.International Journal of Pattern Recognition and Artificial Intelligence, 21(05):961–976, 2007

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.980527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0204313b-6cb0-4395-85f0-678ebc67aeae · outbound

This paper cites Application of covariate shift adaptation techniques in brain–computer interfaces.IEEE Transactions on Biomedical Engineering, 57(6):1318–1324, 2010.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Application of covariate shift adaptation techniques in brain–computer interfaces.IEEE Transactions on Biomedical Engineering, 57(6):1318–1324, 2010

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.794428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d77c0c3c-9b29-4ea4-b952-9290232531fb · outbound

This paper cites Dirichlet-enhanced spam filtering based on biased samples.Advances in neural information processing systems, 19, 2006.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Dirichlet-enhanced spam filtering based on biased samples.Advances in neural information processing systems, 19, 2006

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.716174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 90248572-83e2-499e-9a0d-b87fd468ccaa · outbound

This paper cites Failing loudly: An empirical study of methods for detecting dataset shift.Advances in Neural Information Processing Systems, 32, 2019.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Failing loudly: An empirical study of methods for detecting dataset shift.Advances in Neural Information Processing Systems, 32, 2019

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.697063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6027f7f2-7062-4373-bfe0-bbd9cc869ce7 · outbound

This paper cites A Two-Sample Conditional Distribution Test Using Conformal Prediction and Weighted Rank Sum.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective A Two-Sample Conditional Distribution Test Using Conformal Prediction and Weighted Rank Sum

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:24.345514Z

Source-reported events for the cited work

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Observation aa032fb5-9e27-4b58-ab48-50360d6017b4 · outbound

This paper cites Study on the impact of partition-induced dataset shift onk-fold cross-validation.IEEE Transactions on Neural Networks and Learning Systems, 23(8):1304–1312, 2012.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Study on the impact of partition-induced dataset shift onk-fold cross-validation.IEEE Transactions on Neural Networks and Learning Systems, 23(8):1304–1312, 2012

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.614027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation faebc8d7-7151-4e47-aeb0-ba8b6827c910 · outbound

This paper cites Testing for concept shift online.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Testing for concept shift online

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:08:25.307762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0b9c8771-237a-4e93-9db6-d5aef8b51012 · outbound

This paper cites Testing randomness online.Statistical Science, 36(4):595–611, 2021.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Testing randomness online.Statistical Science, 36(4):595–611, 2021

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.546292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 48e94d1f-15a1-4ca5-9067-8bb64b2a7afe · outbound

This paper cites Cam- bridge University Press, 2012.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Cam- bridge University Press, 2012

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.528278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c0d74161-4ce0-4020-be7b-1beebff25aca · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learning.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Scaffold: Stochastic controlled averaging for federated learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.471534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2e3ed5d3-a7ac-461f-904b-355d88603800 · outbound

This paper cites Federated optimization in heterogeneous networks.Proceedings of Machine learning and systems, 2:429–450, 2020.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Federated optimization in heterogeneous networks.Proceedings of Machine learning and systems, 2:429–450, 2020

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:24.545335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 242f3955-cff0-4436-a642-84c6560a489c · outbound

This paper cites Big data: Principles and best practices of scalable realtime data systems.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Big data: Principles and best practices of scalable realtime data systems

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.357725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a7a664e0-77ba-4275-8416-9e0fd7ada424 · outbound

This paper cites Spark: Cluster computing with working sets.HotCloud, 10(10-10):95, 2010.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Spark: Cluster computing with working sets.HotCloud, 10(10-10):95, 2010

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.197403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ce38820d-6f71-4ecc-a518-4577caac58f0 · outbound

This paper cites Mahout in action: Manning shelter island.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Mahout in action: Manning shelter island

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.136422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9b7d6d5a-ed67-45c2-a33a-47466493c6c8 · outbound

This paper cites Domain-adversarial training of neural networks.Journal of machine learning research, 17(59):1–35, 2016.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Domain-adversarial training of neural networks.Journal of machine learning research, 17(59):1–35, 2016

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:26.075646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cf05a7cd-bf48-4a3e-975d-8fecdd2f8074 · outbound

This paper cites Communication- efficient learning of deep networks from decentralized data.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Communication- efficient learning of deep networks from decentralized data

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:24.739523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bf55fca-50e8-4f8c-8790-c3610b8a664a · outbound

This paper cites These studies, however, do not belong to history yet.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective These studies, however, do not belong to history yet

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:25.917245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4ed51f47-b29c-419e-b62b-35dd374db4f4 · outbound

This paper cites Relative density- ratio estimation for robust distribution comparison.Neural computation, 25(5):1324–1370, 2013.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Relative density- ratio estimation for robust distribution comparison.Neural computation, 25(5):1324–1370, 2013

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:25.863914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c2fcddf7-c2f6-48f1-abc5-329b0c6dd693 · outbound

This paper cites Rethinking importance weighting for deep learning under distribution shift.Advances in neural information processing systems, 33:11996–12007, 2020.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Rethinking importance weighting for deep learning under distribution shift.Advances in neural information processing systems, 33:11996–12007, 2020

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:25.734954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 306c0931-de41-44e1-9d53-d1e8b05e89d7 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks.Proceedings of the national academy of sciences, 114(13):3521–3526, 2017.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Overcoming catastrophic forgetting in neural networks.Proceedings of the national academy of sciences, 114(13):3521–3526, 2017

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:24.879480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e4fbfac-a657-44e6-89bc-69b04803f751 · outbound

This paper cites Tent: Fully Test-time Adaptation by Entropy Minimization.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Tent: Fully Test-time Adaptation by Entropy Minimization

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:24.910596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dfd4b26-c856-4084-9175-7713797a2df2 · outbound

This paper cites Online convex programming and generalized infinitesimal gradient ascent.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Online convex programming and generalized infinitesimal gradient ascent

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:25.642329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f14064c2-b82d-4718-af51-59c9cb522061 · outbound

This paper cites The mnist database of handwritten digits.http://yann.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective The mnist database of handwritten digits.http://yann

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:24.923985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffd359d1-c0ff-4b7c-9cac-f26024e7bb80 · outbound

This paper cites Learning multiple layers of features from tiny images.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Learning multiple layers of features from tiny images

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:24.931117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80aaaa81-86d1-41b6-a5c8-90a79259af82 · outbound

This paper cites Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:24.935938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4fd9d1b-ef03-4974-9fec-4cd464f35c29 · outbound

This paper cites Credit-card-fraud detection-imbalanced-dataset.Kaggle.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Credit-card-fraud detection-imbalanced-dataset.Kaggle

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:25.438871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e6319a81-532e-460a-9dfe-bbce84daf3f9 · outbound

This paper cites OpenML Benchmarking Suites.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective OpenML Benchmarking Suites

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:24.979972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0d1df3c-bd71-466a-a2d2-e089880baac2 · outbound

This paper cites LEAF: A Benchmark for Federated Settings.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective LEAF: A Benchmark for Federated Settings

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:25.069684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdd573f5-2caf-4cc1-9377-50d9464992d5 · outbound

This paper cites Reading digits in natural images with unsupervised feature learning.

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective Reading digits in natural images with unsupervised feature learning

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:25.383984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.