Paper Citation Record · LEDGER

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports

As of 11 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2607.28466.

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

pith.paper-citation-record.v1
2607.28466 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T06:31:32.710103Z

measured 45 of 45 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

45 of 45 outbound references displayed

verified exact9
verified fuzzy0
unresolved34
parse uncertain0
malformed identifier2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 34448512-9ee4-40e1-b825-14a55bbd4548 · outbound

This paper cites CA: A Cancer Journal for Clinicians74(3), 229–263 (2024) https://doi.org/10.3322/caac.21834.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports CA: A Cancer Journal for Clinicians74(3), 229–263 (2024) https://doi.org/10.3322/caac.21834

Reference 1

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Observation 35b983c7-a0d1-4e59-99af-2410631eabbf · outbound

This paper cites New England Journal of Medicine 329(27), 1977–1981 (1993).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports New England Journal of Medicine 329(27), 1977–1981 (1993)

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:31.727121Z

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Observation ff5d4952-d416-44b6-8b05-a10b780e7d1a · outbound

This paper cites New England Journal of Medicine366(8), 687–696 (2012).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports New England Journal of Medicine366(8), 687–696 (2012)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:31.776805Z

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Observation 29e59676-c84c-4a53-9fad-bb50be0e20dd · outbound

This paper cites New England Journal of Medicine387(17), 1547–1556 (2022).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports New England Journal of Medicine387(17), 1547–1556 (2022)

Reference 4

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Observation 9db3faa7-712d-4831-84b4-c26d4151b020 · outbound

This paper cites Gastroenterology155(4), 1069–1078 (2018).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Gastroenterology155(4), 1069–1078 (2018)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:31.864526Z

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Observation 3ae4f1dd-261b-43c9-9ce8-b86ff3942b33 · outbound

This paper cites The lancet Gastroenterology & hepatology4(1), 71–80 (2019).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports The lancet Gastroenterology & hepatology4(1), 71–80 (2019)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:31.906348Z

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Observation 9146c2b8-ccd1-4471-be44-557331aa2303 · outbound

This paper cites Gut68(10), 1813–1819 (2019).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Gut68(10), 1813–1819 (2019)

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:31.970264Z

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Observation ca8b2da7-c925-4b71-bbfd-6dea267aeb41 · outbound

This paper cites Gastroenterology159(2), 512–520 (2020).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Gastroenterology159(2), 512–520 (2020)

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:31.974663Z

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Observation 642cec86-bde2-460c-9743-2881c92b836b · outbound

This paper cites Gastrointestinal Endoscopy97(5), 815–8241 (2023) https://doi.org/10.1016/j.gie.2022.10.016.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Gastrointestinal Endoscopy97(5), 815–8241 (2023) https://doi.org/10.1016/j.gie.2022.10.016

Reference 9

Resolution: verified exact; doi, observed 2026-07-31T06:36:01.033952Z

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Observation f797a7eb-7829-41ee-afb2-f64357bf904d · outbound

This paper cites Medical Image Analysis 98, 103298 (2024) https://doi.org/10.1016/j.media.2024.103298.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Medical Image Analysis 98, 103298 (2024) https://doi.org/10.1016/j.media.2024.103298

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.054104Z

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Observation f391bc13-fc77-49a8-8369-a8828bf2c39e · outbound

This paper cites IEEE Transactions on Medical Imaging44(12), 5245–5257 (2025).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports IEEE Transactions on Medical Imaging44(12), 5245–5257 (2025)

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.110782Z

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Observation 60845a3b-e326-4ec8-a865-c304e8ffdcd4 · outbound

This paper cites Nature622(7981), 156–163 (2023) https://doi.org/10.1038/s41586-023-06555-x.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Nature622(7981), 156–163 (2023) https://doi.org/10.1038/s41586-023-06555-x

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.167354Z

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Observation 28bcbdce-66e3-468a-8e49-cbcd82eff4ab · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports In: International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp

Reference 13

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Observation d555956d-93af-4246-98d3-167d487bfd55 · outbound

This paper cites In: Proceedings of the 38th International Conference on Machine Learning.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports In: Proceedings of the 38th International Conference on Machine Learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.316428Z

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Observation e9e13ab3-bbcf-4d5e-8e06-dd6cde682778 · outbound

This paper cites In: Proceedings of the 38th International Conference on Machine Learning.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports In: Proceedings of the 38th International Conference on Machine Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.373693Z

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Observation d80ac083-88c9-4f8b-8127-d181805851e3 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.428454Z

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Observation 64b678bf-a1be-4b4c-870f-f63f01061c52 · outbound

This paper cites In: Machine Learning for Healthcare Conference (MLHC) (2022).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports In: Machine Learning for Healthcare Conference (MLHC) (2022)

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.485580Z

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Observation 6e455d68-fee6-4362-b76b-27d16b9805a0 · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.539390Z

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Observation 306a20be-fbb3-40fd-90db-44c18f849a6e · outbound

This paper cites Nature Biomedical Engineering6(12), 1399–1406 (2022).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Nature Biomedical Engineering6(12), 1399–1406 (2022)

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.592810Z

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Observation 51843c6d-6bbc-475c-9f70-1bcced64e18e · outbound

This paper cites Nature Medicine29(9), 2307–2316 (2023).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Nature Medicine29(9), 2307–2316 (2023)

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.642717Z

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Observation d804245e-fa1e-43e1-879e-dda53f1be600 · outbound

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Nature Medicine30(3), 863–874 (2024)

Reference 21

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Observation 9a52d7d8-c409-4c99-a346-9031823549f4 · outbound

This paper cites Nature Biomedical Engineering (2026) https://doi.org/10.1038/s41551-025-01599-y.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Nature Biomedical Engineering (2026) https://doi.org/10.1038/s41551-025-01599-y

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.647850Z

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Observation 5db9b97c-48f4-4efb-ae66-c3b3dfb7460d · outbound

This paper cites Nature Biomedical Engineering (2025) https://doi.org/10.1038/s41551-025-01500-x.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Nature Biomedical Engineering (2025) https://doi.org/10.1038/s41551-025-01500-x

Reference 23

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Observation 033f78f3-ada8-41ae-a057-16375d2f268e · outbound

This paper cites Figshare.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Figshare

Reference 24

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Observation 348d3bdb-869f-42d7-8d18-247f561ff82f · outbound

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Figshare

Reference 25

Resolution: verified exact; doi, observed 2026-07-31T06:36:00.815198Z

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Observation 1a20e004-87e3-4629-85cc-25a34fc07e64 · outbound

This paper cites In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023, pp.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023, pp

Reference 26

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Observation a906e53f-1a83-4446-a197-0576dad29520 · outbound

This paper cites Gastrointestinal Endoscopy 58(6), 3–43 (2003) https://doi.org/10.1016/S0016-5107(03)02159-X.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Gastrointestinal Endoscopy 58(6), 3–43 (2003) https://doi.org/10.1016/S0016-5107(03)02159-X

Reference 27

Resolution: verified exact; doi, observed 2026-07-31T06:36:00.623177Z

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Observation c054943b-bfc1-420d-81ad-ffb94ab777fc · outbound

This paper cites Gastrointestinal Endoscopy78(4), 625–632 (2013) https://doi.org/10.1016/j.gie.2013.04.185.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Gastrointestinal Endoscopy78(4), 625–632 (2013) https://doi.org/10.1016/j.gie.2013.04.185

Reference 28

Resolution: verified exact; doi, observed 2026-07-31T06:36:00.527081Z

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Observation ff50136f-0f9c-466a-9b85-36d6b2a4c1f8 · outbound

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Gastroenterology158(4), 1131–1153 (2020) https://doi.org/10.1053/j.gastro.2019.10.026

Reference 29

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Observation 8f5b7d43-ad0b-4e5b-8b7b-a5111af2febe · outbound

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports NEJM AI2(1) (2025) https://doi.org/10.1056/ AIoa2400640

Reference 30

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This paper cites Clinical and Translational Gastroenterology 12(1), 00282 (2020) https://doi.org/10.14309/ctg.0000000000000282.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Clinical and Translational Gastroenterology 12(1), 00282 (2020) https://doi.org/10.14309/ctg.0000000000000282

Reference 31

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Observation 9503bc53-a156-4e59-9698-fcbfc95eb341 · outbound

This paper cites npj Digital Medicine9(1), 394 (2026) https: //doi.org/10.1038/s41746-026-02569-7.

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports npj Digital Medicine9(1), 394 (2026) https: //doi.org/10.1038/s41746-026-02569-7

Reference 32

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Observation 849f05f1-5c66-41d7-b864-694ec995fab1 · outbound

This paper cites arXiv preprint arXiv:2601.08183 (2026).

A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports arXiv preprint arXiv:2601.08183 (2026)

Reference 33

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports In: Medical Image Computing and Computer Assisted Intervention 22 – MICCAI 2024

Reference 34

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports In: International Conference on Learning Representations (ICLR) (2021)

Reference 35

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Observation ff6b7643-4770-4536-900e-2187ed4593c8 · outbound

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Advances in Neural Information Processing Systems (2017)

Reference 36

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Observation 7eaac811-c70e-4739-8ce1-dc557ec3720a · outbound

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Representation Learning with Contrastive Predictive Coding

Reference 37

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports In: Interna- tional Conference on Learning Representations (ICLR) (2019)

Reference 38

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Observation 2a3adefe-1868-4ebe-9238-cbb0658bdbcd · outbound

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports ACM Transactions on Computing for Healthcare3(1), 1–23 (2021)

Reference 39

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Observation 35845eab-dbe0-4afd-a253-68706cf9d2fa · outbound

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports saliency maps from physicians

Reference 40

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Journal of Healthcare Engineering2017, 4037190 (2017)

Reference 41

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports In: International Conference on Multimedia Modeling, pp

Reference 42

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Observation 36410a94-0c31-4df5-ad82-928da6c3cce0 · outbound

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Scientific Data 10(1), 75 (2023)

Reference 43

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Observation d08a715c-442c-4e5a-a5fe-d602a6cf3368 · outbound

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports Journal of Machine Learning Research9, 2579–2605 (2008) 23

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-31T06:31:32.710103Z

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A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports https://doi.org/10.1007/978-3-031-43993-3 51

Reference 536

Resolution: verified exact; doi, observed 2026-07-31T06:36:00.720650Z

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Pith citing papers

No inbound Pith citation observations are available.