Paper Citation Record · LEDGER

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction

As of 7 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2608.00071.

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

pith.paper-citation-record.v1
2608.00071 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T01:29:14.184272Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

25 of 25 outbound references displayed

verified exact1
verified fuzzy0
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6b647a85-21c0-4ed7-a406-3b88f4b04c2a · outbound

This paper cites Journal of Clinical Oncology37(18), 1578–1589 (2019) Empirical investigation of 3D CT Foundation Models 13.

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Journal of Clinical Oncology37(18), 1578–1589 (2019) Empirical investigation of 3D CT Foundation Models 13

Reference 1

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Observation 5ed65d26-d8ee-4c0c-ac47-fcddca8ae3f1 · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention.

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:11.601519Z

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Observation 444a3ae6-ec9d-4694-a1cc-d78378b8ce95 · outbound

This paper cites Physics and Imaging in Radiation Oncology25, 100404 (2023).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Physics and Imaging in Radiation Oncology25, 100404 (2023)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:11.735561Z

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Observation aebce1e3-4583-4d41-bacb-cdd5a694ff3d · outbound

This paper cites In: International conference on machine learning.

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction In: International conference on machine learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:11.878807Z

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Observation 46d333d6-31f3-4f00-8554-78b9a455525f · outbound

This paper cites In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:11.984880Z

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Observation b83806df-17c4-47cb-a985-6fdd78fb8046 · outbound

This paper cites bmj 384(2024).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction bmj 384(2024)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:12.099825Z

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Observation fbc484a9-6a2c-4b35-8652-88eb52061abb · outbound

This paper cites Trans- lational oncology14(1), 100906 (2021).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Trans- lational oncology14(1), 100906 (2021)

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:12.194900Z

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Observation 64e11712-c072-41b0-9fe4-db279c0c8931 · outbound

This paper cites Nature Biomedical Engineering pp.

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Nature Biomedical Engineering pp

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:12.302788Z

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Observation 49cac1d3-2aa5-4460-89cf-5d14e9ba8945 · outbound

This paper cites In: Proceedings of the Computer Vision and Pattern Recognition Conference.

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction In: Proceedings of the Computer Vision and Pattern Recognition Conference

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:12.340954Z

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Observation 9204c726-7908-4314-b909-8e52f5ef46a5 · outbound

This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:12.464831Z

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Observation 57c8b630-08b2-49df-84ae-22796a434893 · outbound

This paper cites Nature reviews Clinical oncology14(12), 749–762 (2017).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Nature reviews Clinical oncology14(12), 749–762 (2017)

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:12.558786Z

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Observation 051ed88f-7292-458b-a3d5-5ca0c668aa80 · outbound

This paper cites Scientific reports12(1), 3183 (2022).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Scientific reports12(1), 3183 (2022)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:12.648201Z

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Observation fe23de0a-f3d7-4276-8813-06d79f26afbb · outbound

This paper cites How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks?.

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks?

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:12.745197Z

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Observation 04d59574-6ab0-4ddb-822a-695b6dd268ef · outbound

This paper cites Cancers14(7), 1674 (2022) 14 B.

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Cancers14(7), 1674 (2022) 14 B

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:12.828163Z

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Observation b64f1be5-8ecf-4394-a9ed-eae3257e9697 · outbound

This paper cites Vision Foundation Models for Computed Tomography.

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Vision Foundation Models for Computed Tomography

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:12.924854Z

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Observation 168f6b16-7865-4e7e-a72d-4e3d6b7b071d · outbound

This paper cites Radiation Oncology15(1), 81 (2020).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Radiation Oncology15(1), 81 (2020)

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:13.008207Z

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Observation 54203af6-a93e-476f-856c-b8a9843da407 · outbound

This paper cites Cancer Medicine 14(6), e70706 (2025).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Cancer Medicine 14(6), e70706 (2025)

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:13.144836Z

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Observation 16699cd0-8a9c-4d61-a39c-1bd6a165a517 · outbound

This paper cites Ad- vances in neural information processing systems30(2017).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Ad- vances in neural information processing systems30(2017)

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:13.272234Z

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Observation a7000a01-1564-4626-8b0f-bc9750849588 · outbound

This paper cites Health Economics Review15(1), 84 (2025).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Health Economics Review15(1), 84 (2025)

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:13.394844Z

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Observation db4b3522-9d66-4b87-ac4d-fa753b8bfd2b · outbound

This paper cites Frontiers in oncology12, 974467 (2022).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Frontiers in oncology12, 974467 (2022)

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:13.554754Z

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Observation c911e369-38c0-4a76-af9b-29a659b58834 · outbound

This paper cites Scientific reports7(1), 10117 (2017).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Scientific reports7(1), 10117 (2017)

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:13.711408Z

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Observation 1ecda507-15aa-4e5c-a871-32aee217a236 · outbound

This paper cites Advances in neural information pro- cessing systems30(2017).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Advances in neural information pro- cessing systems30(2017)

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:13.768914Z

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Observation 1a68fff2-b0aa-4d5f-a50f-14f5f962a979 · outbound

This paper cites Medical Physics51(4), 3101–3109 (2024).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Medical Physics51(4), 3101–3109 (2024)

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:13.924748Z

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Observation 5832c618-dcda-4c52-9b9c-75822d3760a6 · outbound

This paper cites The Cancer Imaging Archive4(2023).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction The Cancer Imaging Archive4(2023)

Reference 24

Resolution: verified exact; doi, observed 2026-08-04T01:34:17.439635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2e3c5960-b5ce-4464-b14d-e8916c8d2d12 · outbound

This paper cites Scientific reports 6(1), 23428 (2016).

Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction Scientific reports 6(1), 23428 (2016)

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T01:29:14.184272Z

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Pith citing papers

No inbound Pith citation observations are available.