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Paper Citation Record · LEDGER

A Generalised and Adaptable Reinforcement Learning Stopping Method

As of 22 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2505.01907.

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

pith.paper-citation-record.v1
2505.01907 v2

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

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measured 46 of 46 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

46 of 46 outbound references displayed

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External citation measurements

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Outbound references

Observation 99b33b39-32cb-4ced-98a3-b7d91180a8e1 · outbound

This paper cites ACM Computing Surveys 55(7), 1–38 (2022).

A Generalised and Adaptable Reinforcement Learning Stopping Method ACM Computing Surveys 55(7), 1–38 (2022)

Reference 1

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This paper cites IEEE Signal Processing Magazine 34(6), 26–38 (2017).

A Generalised and Adaptable Reinforcement Learning Stopping Method IEEE Signal Processing Magazine 34(6), 26–38 (2017)

Reference 2

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This paper cites Providing More Efficient Access To Government Records: A Use Case Involving Application of Machine Learning to Improve FOIA Review for the Deliberative Process Privilege.

A Generalised and Adaptable Reinforcement Learning Stopping Method Providing More Efficient Access To Government Records: A Use Case Involving Application of Machine Learning to Improve FOIA Review for the Deliberative Process Privilege

Reference 3

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This paper cites In: Proceedings of the 26th Annual International Conference on Machine Learning.

A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of the 26th Annual International Conference on Machine Learning

Reference 4

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This paper cites In: Find- ings of the Association for Computational Linguistics: EMNLP 2023.

A Generalised and Adaptable Reinforcement Learning Stopping Method In: Find- ings of the Association for Computational Linguistics: EMNLP 2023

Reference 5

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This paper cites In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (2024).

A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (2024)

Reference 6

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This paper cites Using Chao's Estimator as a Stopping Criterion for Technology-Assisted Review.

A Generalised and Adaptable Reinforcement Learning Stopping Method Using Chao's Estimator as a Stopping Criterion for Technology-Assisted Review

Reference 7

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This paper cites Systematic Reviews 9(1), 1–14 (2020).

A Generalised and Adaptable Reinforcement Learning Stopping Method Systematic Reviews 9(1), 1–14 (2020)

Reference 8

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This paper cites Autonomy and Reliability of Continuous Active Learning for Technology-Assisted Review.

A Generalised and Adaptable Reinforcement Learning Stopping Method Autonomy and Reliability of Continuous Active Learning for Technology-Assisted Review

Reference 9

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This paper cites In: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval.

A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval

Reference 10

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This paper cites In: Proceedings of the 25th ACM interna- tional on conference on information and knowledge management.

A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of the 25th ACM interna- tional on conference on information and knowledge management

Reference 11

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This paper cites In: Proceedings of The Nineteenth Text REtrieval Conference, TREC 2010, Gaithersburg, Maryland, USA, November 16-19, 2010.

A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of The Nineteenth Text REtrieval Conference, TREC 2010, Gaithersburg, Maryland, USA, November 16-19, 2010

Reference 12

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A Generalised and Adaptable Reinforcement Learning Stopping Method In: European Conference on Information Retrieval

Reference 13

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This paper cites In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval.

A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval

Reference 14

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This paper cites In: Proceedings of The Twenty-Fifth Text REtrieval Conference, TREC.

A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of The Twenty-Fifth Text REtrieval Conference, TREC

Reference 15

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A Generalised and Adaptable Reinforcement Learning Stopping Method John Wiley & Sons (2019)

Reference 16

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A Generalised and Adaptable Reinforcement Learning Stopping Method In: Working Notes of CLEF 2017 - Conference and Labs of the Evaluation Forum

Reference 17

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This paper cites Journal of the American Statistical Association 47(260), 663–685 (1952).

A Generalised and Adaptable Reinforcement Learning Stopping Method Journal of the American Statistical Association 47(260), 663–685 (1952)

Reference 18

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A Generalised and Adaptable Reinforcement Learning Stopping Method Environment International 138, 105623 (2020), https: //www.sciencedirect.com/science/article/pii/S0160412019314023

Reference 19

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A Generalised and Adaptable Reinforcement Learning Stopping Method In: CEUR workshop proceedings

Reference 20

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A Generalised and Adaptable Reinforcement Learning Stopping Method In: CEUR workshop proceedings

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A Generalised and Adaptable Reinforcement Learning Stopping Method In: CEUR workshop proceedings

Reference 22

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A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management (2021)

Reference 23

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A Generalised and Adaptable Reinforcement Learning Stopping Method Journal of Machine Learning Research 5, 361– 397 (2004)

Reference 24

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A Generalised and Adaptable Reinforcement Learning Stopping Method ACM Trans

Reference 25

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A Generalised and Adaptable Reinforcement Learning Stopping Method Encyclopedia of machine learning 2011, 231–235 (2008)

Reference 26

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A Generalised and Adaptable Reinforcement Learning Stopping Method Journal of the Association for Information Science and Technology 70(1), 49–60 (2019)

Reference 27

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A Generalised and Adaptable Reinforcement Learning Stopping Method ACM Transactions on Information Systems (TOIS) 39(1), 1–34 (2020)

Reference 28

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A Generalised and Adaptable Reinforcement Learning Stopping Method Data Mining and Knowledge Discovery pp

Reference 30

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A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval

Reference 31

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A Generalised and Adaptable Reinforcement Learning Stopping Method Journal of Ma- chine Learning Research 22(268), 1–8 (2021), http://jmlr.org/papers/v22/20- 1364.html

Reference 32

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This paper cites In: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval.

A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval

Reference 33

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A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of the 31st Interna- tional Conference on Distributed Computing Systems workshops

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-16T04:13:02.272396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T04:13:01.668979Z digest=sha256:2944dd91e62b396645761d25050fa50fa7e8632c2dc9f15058067b897b2f30b9

Observation 2692291d-a97b-4042-8d7c-1ddf512a48e2 · outbound

This paper cites Proximal Policy Optimization Algorithms.

A Generalised and Adaptable Reinforcement Learning Stopping Method Proximal Policy Optimization Algorithms

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-16T04:13:01.674287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:13:01.674287Z digest=sha256:1d3a339e9dbe11bf31731392a82b6b28bb499138dd39d1cda5f6613f5bf941c1

Observation 85ff92ba-2f7a-442c-b929-8340573fad78 · outbound

This paper cites Research Synthesis Methods 5(1), 31–49 (2014).

A Generalised and Adaptable Reinforcement Learning Stopping Method Research Synthesis Methods 5(1), 31–49 (2014)

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:13:02.257625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T04:13:01.679099Z digest=sha256:72b171427039b84819ad2844185e063cab3b97814dcde7066a9d825389c14255

Observation 58512207-52b6-4fd8-b993-24cc27dc5650 · outbound

This paper cites ACM Transactions on Information Systems 42(3), 1–37 (2023), https://doi.org/10.1145/3631990.

A Generalised and Adaptable Reinforcement Learning Stopping Method ACM Transactions on Information Systems 42(3), 1–37 (2023), https://doi.org/10.1145/3631990

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-16T04:13:01.683567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:13:01.683567Z digest=sha256:c209268f324e8641273d2987c520e6dae8d694fd77cd75a7a1b95a4af93e8278

Observation 16ca08c9-5341-48d4-ba43-e7d06acd9e55 · outbound

This paper cites The MIT Press, Cambridge (2018).

A Generalised and Adaptable Reinforcement Learning Stopping Method The MIT Press, Cambridge (2018)

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:13:02.241977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T04:13:01.688104Z digest=sha256:370824e2982c0bb4350c248a6b176d1a2fa582a26935ba0aba0459d2a1993bf7

Observation 69e71dca-734f-4bab-b286-74106cca2c82 · outbound

This paper cites John Wiley & Sons, Hoboken, New Jersey (2012).

A Generalised and Adaptable Reinforcement Learning Stopping Method John Wiley & Sons, Hoboken, New Jersey (2012)

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:13:02.225709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T04:13:01.693427Z digest=sha256:d48ca27a13f13fb0e6247b56925db0e16520bb714793c4d0033245b1cada81ee

Observation a0cf0ba9-b2cf-4401-a885-b3f3eb11e207 · outbound

This paper cites an unresolved cited work.

A Generalised and Adaptable Reinforcement Learning Stopping Method Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-16T04:13:01.697697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:13:01.697697Z digest=sha256:5c302e2308d439d985809f8013ba605b478bb1af91f63fe0a99951f4d847f7d3

Observation e6e8fcc3-dfaf-41eb-9448-8c340693f12b · outbound

This paper cites Machine Learning 8, 229–256 (1992).

A Generalised and Adaptable Reinforcement Learning Stopping Method Machine Learning 8, 229–256 (1992)

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:13:02.210746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T04:13:01.702086Z digest=sha256:2180cfa85b2ee82b0f3e107e15c92ec3a211b6c08ebd6fbb55fc686c733e6d2b

Observation 3d116ddf-a4a3-4c9c-9ed6-a2dc5dcd9c76 · outbound

This paper cites In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval.

A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:13:02.195217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T04:13:01.706998Z digest=sha256:ae3483a96ef3d83a1657e23c541a10c33c412d28527b591a9e411c72fa3946ea

Observation dd2173da-2674-4bca-8e56-5c0caa8d8910 · outbound

This paper cites In: Proceedings of the 21st ACM Symposium on Document Engineer- ing 2021 (DocEng ’21).

A Generalised and Adaptable Reinforcement Learning Stopping Method In: Proceedings of the 21st ACM Symposium on Document Engineer- ing 2021 (DocEng ’21)

Reference 44

Resolution
metadata mismatch
raw_fallback, observed 2026-08-16T04:13:01.851988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T04:13:01.717454Z digest=sha256:73b01823f68717733debee84fdbcb9b01e41d64087b7f1618a1c0821dc70a579

Observation d01668ee-74fc-408f-aea9-9196336ad7c3 · outbound

This paper cites In: 2nd International Conference on Design of Experimental Search & Information REtrieval Systems (DESIRES 2021).

A Generalised and Adaptable Reinforcement Learning Stopping Method In: 2nd International Conference on Design of Experimental Search & Information REtrieval Systems (DESIRES 2021)

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:13:02.179661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T04:13:01.722006Z digest=sha256:af2b7f0da788f9a45953cf90150c148e82f07fd46bbf31e086d2b94348f701b1

Observation acd654ea-e568-40ba-a1c5-2f00b840e19d · outbound

This paper cites Expert Systems with Applications 120, 57–71 (2019).

A Generalised and Adaptable Reinforcement Learning Stopping Method Expert Systems with Applications 120, 57–71 (2019)

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:13:02.162458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T04:13:01.726690Z digest=sha256:add3dbdaedf4537412cd2d43728400e857c7c5d20c5b7a4fd720daf89b04c26d

Observation e361ea46-7bf8-4683-99bd-0b953ca6d098 · outbound

This paper cites an unresolved cited work.

A Generalised and Adaptable Reinforcement Learning Stopping Method Unresolved cited work

Reference 2016

Resolution
unresolved
raw_fallback, observed 2026-08-16T04:13:02.528331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T04:13:01.580678Z digest=sha256:a8b3951a435f2886338bf04a2e6848cdea6f932e109dc7c9a977f6ee8ae7a664

Pith citing papers

No inbound Pith citation observations are available.