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Paper Citation Record · LEDGER

Ribbon: Scalable Approximation and Robust Uncertainty Quantification

As of 11 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2606.27269.

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

pith.paper-citation-record.v1
2606.27269 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T02:00:55.202866Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

54 of 54 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved52
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ceb08d50-f59c-4429-8927-0063870158c7 · outbound

This paper cites 1986 , publisher=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification 1986 , publisher=

Reference 1

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Observation e26885b8-daad-457e-bb6f-49ff85733994 · outbound

This paper cites Journal of the American Statistical Association , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Journal of the American Statistical Association , volume=

Reference 2

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Observation 2d3822c6-954a-4bb5-8d53-58f6fa292fa8 · outbound

This paper cites 2009 , publisher=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification 2009 , publisher=

Reference 3

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Observation ee145d70-2a29-4a70-b8a9-52ae79de4696 · outbound

This paper cites Technometrics , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Technometrics , volume=

Reference 4

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Observation 2a33dbfc-a28d-4a34-82cf-e0314b8aa591 · outbound

This paper cites Technometrics , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Technometrics , volume=

Reference 5

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Observation 4f481ba4-482f-4fbb-914c-6d6366c2aba0 · outbound

This paper cites Annals of Statistics , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Annals of Statistics , volume=

Reference 6

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Observation 6c46c8d4-cccb-4c24-945b-c10aa961b7db · outbound

This paper cites 1993 , address=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification 1993 , address=

Reference 7

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Observation 626b9a75-ed18-4690-8a9c-a3de3ee6733b · outbound

This paper cites 1998 , publisher=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification 1998 , publisher=

Reference 8

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Observation 24521cba-2698-400a-8021-92d5cd912fd3 · outbound

This paper cites Econometrica , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Econometrica , volume=

Reference 9

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Observation 888aed0a-829b-48e0-ae71-cbdd7a0ceefe · outbound

This paper cites Econometric Computing with.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Econometric Computing with

Reference 10

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Observation b717ed9e-3489-4360-9dbe-abb8eb4a1a69 · outbound

This paper cites Neural Computation , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Neural Computation , volume=

Reference 11

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Observation 69f82885-653d-44fc-adca-faa5a4c8236e · outbound

This paper cites an unresolved cited work.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Unresolved cited work

Reference 12

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Observation 1fecb1e9-8200-44c6-a5a2-8f8f02d581d9 · outbound

This paper cites Proceedings of the 32nd International Conference on Machine Learning (ICML) , pages=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Proceedings of the 32nd International Conference on Machine Learning (ICML) , pages=

Reference 13

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Observation b00e18a2-45b3-4db8-9afb-085053c5d2eb · outbound

This paper cites Proceedings of the 33rd International Conference on Machine Learning (ICML) , pages=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Proceedings of the 33rd International Conference on Machine Learning (ICML) , pages=

Reference 14

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification 6th International Conference on Learning Representations (ICLR) , year=

Reference 15

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Observation 1a3bbbab-3fad-4766-81d2-a66f2d7f3175 · outbound

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Proceedings of the 34th International Conference on Machine Learning (ICML) , pages=

Reference 16

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Observation d570d983-a20c-4c72-a7cd-7d2e0f470274 · outbound

This paper cites Proceedings of the 33rd International Conference on Neural Information Processing Systems (NeurIPS) , year=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Proceedings of the 33rd International Conference on Neural Information Processing Systems (NeurIPS) , year=

Reference 17

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Observation e0937271-6af7-4f1b-b36d-addb3de5acf2 · outbound

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification 9th International Conference on Learning Representations (ICLR) , year=

Reference 18

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Observation 9dcf25f8-b438-4fa8-8315-e4c39217bfa0 · outbound

This paper cites Journal of Machine Learning Research , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Journal of Machine Learning Research , volume=

Reference 19

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Observation ebed565c-9918-43b3-a1bb-9a9dd222ea6f · outbound

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Advances in Neural Information Processing Systems (NeurIPS) , volume=

Reference 20

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Unresolved cited work

Reference 21

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification International Conference on Learning Representations (ICLR) , year =

Reference 22

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Observation aeefb851-a805-4099-aa91-f2701aec8ba2 · outbound

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Journal of the American Statistical Association , volume=

Reference 23

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Observation 2df6a29c-d7d4-4c0d-ba43-4c26cf6c2d97 · outbound

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Advances in Neural Information Processing Systems , volume=

Reference 24

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Information Fusion , volume=

Reference 25

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification 2024 , edition=

Reference 26

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification 2013 , publisher=

Reference 27

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Observation e1662d35-b47b-4922-be37-17e61d07827d · outbound

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Two tests for sequential detection of a change-point in a nonlinear model

Reference 28

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification International Conference on Machine Learning , pages=

Reference 29

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification International Conference on Machine Learning , pages=

Reference 30

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Annals of Statistics , volume=

Reference 31

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Observation 2101784a-f46d-4593-8d72-1e046738e080 · outbound

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Annals of Statistics , volume=

Reference 32

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Observation 69ba0c48-2848-4c13-b0dd-984afb50862d · outbound

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Journal of the Royal Statistical Society: Series B (Methodological) , volume=

Reference 33

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Journal of the Royal Statistical Society: Series B (Methodological) , volume=

Reference 34

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification International Conference on Machine Learning , pages=

Reference 35

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Advances in Neural Information Processing Systems , volume=

Reference 36

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification Constraining the orientation of the spin axes of extrasolar minor bodies 1I/2017 U1 (`Oumuamua) and 2I/Borisov

Reference 37

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Observation 93e05faa-b079-4b24-9c41-aa8c19113385 · outbound

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification International Conference on Machine Learning , pages=

Reference 38

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Ribbon: Scalable Approximation and Robust Uncertainty Quantification International Conference on Machine Learning , pages=

Reference 39

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:942167a1c528f445c8e9b6c74f7d04e0eb54bb2dc66d31bf66b2f2bc5ccb4da5

Observation 56180200-3999-4554-b04d-e370d0504c0a · outbound

This paper cites International Conference on Machine Learning , pages=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification International Conference on Machine Learning , pages=

Reference 40

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:88ef6db553e62bba59b69c7f7743f258b5c892ecd5d739e0d8ab72fe72d29599

Observation df4f6681-7040-4fd0-a53d-a18e57e9591a · outbound

This paper cites Neural Computation , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Neural Computation , volume=

Reference 41

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no resolver link, observed 2026-06-26T02:00:55.202866Z

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:3e656f8d8bef3c7a04adf86019e74014560ea0e7afd0ccf2c02ab4b97ec80218

Observation 295ff254-a19c-491f-aef8-69854999cc4c · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Advances in Neural Information Processing Systems , volume=

Reference 42

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no resolver link, observed 2026-06-26T02:00:55.202866Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:c3b1c0c9d13c64dbce45f57b53c430eb8955a232417b94ff8369d320bc28079c

Observation d54d7aac-0301-42b6-94d9-495a6d036c63 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Advances in Neural Information Processing Systems , volume=

Reference 43

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no resolver link, observed 2026-06-26T02:00:55.202866Z

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:ca9701d6214d57fd00d2cebab673b9530807c179bd457d6a564748793f4a7aaf

Observation 31b3b4a5-228e-47a2-8970-0d8b4be718fb · outbound

This paper cites International Conference on Machine Learning , pages=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification International Conference on Machine Learning , pages=

Reference 44

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no resolver link, observed 2026-06-26T02:00:55.202866Z

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:6ef1e549a0cf1ebe5ef98a4ecf5b8594fa1d533c006cf69cdef9b6d24b509e74

Observation 47514090-181b-4585-8b8c-c69bb139703e · outbound

This paper cites International Conference on Learning Representations , year=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification International Conference on Learning Representations , year=

Reference 45

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:80e7dc584a4e2ba1f0b5ae6393a1ce450fd2fef2cf6a489974b11a2773688afd

Observation f80f119a-1c84-4285-badc-efbf46b852e3 · outbound

This paper cites Proceedings of the Conference on Uncertainty in Artificial Intelligence , year=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Proceedings of the Conference on Uncertainty in Artificial Intelligence , year=

Reference 46

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:267870ca5d15ec0af6980cf00ed04789e3afc22bf0bb53c3f5fc07ea2dfb0270

Observation fd321f84-c515-4806-bcb4-c49e38d4833f · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Advances in Neural Information Processing Systems , volume=

Reference 47

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:308552b09ebe6cf1234ab10c86022a3bc860980a44ebda6421b25bfb4d88bca0

Observation 14f1172c-0f7c-4f2a-8e72-18aa7c4f8bee · outbound

This paper cites 2005 , publisher=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification 2005 , publisher=

Reference 48

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:60587721bde25cfa59f415865a2c78ab3c03e2f5627738041b9d56d5fb5fa584

Observation fc036f33-5a34-475d-ba09-98fd7f440ae5 · outbound

This paper cites Journal of the American Statistical Association , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Journal of the American Statistical Association , volume=

Reference 49

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:23f41468daaee9a6df6e576888d50ebe16869516d96d937629701f9694e09575

Observation 59750481-e67e-43dc-8e68-b69b1ba46f8e · outbound

This paper cites Annals of Statistics , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Annals of Statistics , volume=

Reference 50

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:51f300bdb0cc1ca3ffe86bc5692ecd7a81fc7caaf5432bc84af3d7fd926e7e31

Observation 2627b53e-b792-442a-83b1-fdbd1f0b1901 · outbound

This paper cites International Conference on Machine Learning , pages=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification International Conference on Machine Learning , pages=

Reference 51

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:5669023327e68db84776ef01b22d9b1a07812ac088c7eb1700823eda0ca8c133

Observation 7bbd4faf-47e5-4159-aaaa-d738e5ccf24a · outbound

This paper cites Advances in neural information processing systems , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Advances in neural information processing systems , volume=

Reference 52

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:b6b87cb1ad151dcd831fe5e6354790e16f637ba99075639db9bec84bd5068a76

Observation a38687b9-977d-46b8-86cf-10dbfbfc782a · outbound

This paper cites Statistical Science , volume=.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Statistical Science , volume=

Reference 53

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:76eb72043f383baa43202e5e77d5515e141f259667e8781889acc30631c19f6b

Observation 3da468c1-5393-481c-8a12-e68dd714dd0e · outbound

This paper cites Proceedings of the 38th International Conference on Machine Learning , pages =.

Ribbon: Scalable Approximation and Robust Uncertainty Quantification Proceedings of the 38th International Conference on Machine Learning , pages =

Reference 54

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source=arxiv_source observed=2026-06-26T02:00:55.202866Z digest=sha256:6033a3bfb0b0448f2f6ede4350d61ef5b1cf39d4b86b1a162ce20d4cf05918a0

Pith citing papers

No inbound Pith citation observations are available.