Paper Citation Record · LEDGER

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift

As of 8 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2607.10358.

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

pith.paper-citation-record.v1
2607.10358 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T12:21:48.661331Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

35 of 35 outbound references displayed

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verified fuzzy0
unresolved35
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External citation measurements

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Outbound references

Observation 2c5cf1dc-c031-422b-8cd6-13c2b84dbab9 · outbound

This paper cites Data6(11), 111 (2021).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Data6(11), 111 (2021)

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation b0c396d5-e14d-49f5-93c8-289b346f483d · outbound

This paper cites an unresolved cited work.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 4326bb5c-484b-4c08-957f-af299d6d7502 · outbound

This paper cites Data in Brief55, 110633 (2024).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Data in Brief55, 110633 (2024)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation b893d5d3-b5f1-40f4-a574-6c555a6c853a · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift On the Opportunities and Risks of Foundation Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 632ce889-35d6-4aef-a2d4-8f0754fae36d · outbound

This paper cites JAMA Network Open4(8), e2119100 (2021).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift JAMA Network Open4(8), e2119100 (2021)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 7ec0941a-3c91-4255-a7a7-02f2519f4411 · outbound

This paper cites Scientific Data10(1), 123 (2023).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Scientific Data10(1), 123 (2023)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 559d9aa3-1e37-476f-a2cd-16aac6ae2506 · outbound

This paper cites Multi-View and Multi-Scale Alignment for Contrastive Language-Image Pre-training in Mammography.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Multi-View and Multi-Scale Alignment for Contrastive Language-Image Pre-training in Mammography

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 9e07652e-8bea-4fcd-9d95-d4acebe86c34 · outbound

This paper cites GLAM: Geometry-Guided Local Alignment for Multi-View VLP in Mammography.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift GLAM: Geometry-Guided Local Alignment for Multi-View VLP in Mammography

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 29bf5e24-1723-47f7-8753-a5e85ccfa454 · outbound

This paper cites Bias and Generalizability of Foundation Models across Datasets in Breast Mammography.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Bias and Generalizability of Foundation Models across Datasets in Breast Mammography

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation bbfad378-b5af-4dca-a30c-ba43651a742a · outbound

This paper cites In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2024, pp.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2024, pp

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 629786d5-c152-4769-a778-d0f28372c71f · outbound

This paper cites Mammo-FM: Breast-specific foundational model for Integrated Mammographic Diagnosis, Prognosis, and Reporting.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Mammo-FM: Breast-specific foundational model for Integrated Mammographic Diagnosis, Prognosis, and Reporting

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 4052fd9e-0b20-4538-b55b-d62229113e1d · outbound

This paper cites Radiology: Artificial Intelligence5(6), e230060 (2023).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Radiology: Artificial Intelligence5(6), e230060 (2023)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 90f9b5ba-1722-4f01-a9f3-ababf956a5cc · outbound

This paper cites Radiology: Artificial Intelligence3(1), e200103 (2021).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Radiology: Artificial Intelligence3(1), e200103 (2021)

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 1d8a72bb-ca41-4ac1-ad95-5f5b659c6f92 · outbound

This paper cites In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 77f84011-8469-4218-8fdd-5aa03e29f3e4 · outbound

This paper cites arXiv preprint arXiv:2509.20271 (2025).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift arXiv preprint arXiv:2509.20271 (2025)

Reference 15

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Observation 458909af-930b-4d3a-8e21-428b9e1e5bc1 · outbound

This paper cites Radiology: Artificial Intelligence5(1), e220047 (2023).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Radiology: Artificial Intelligence5(1), e220047 (2023)

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation b501c151-12f7-429b-b6cb-05530da1f96e · outbound

This paper cites Scientific Data12(1), 1479 (2025).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Scientific Data12(1), 1479 (2025)

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 4874232b-cb77-4d74-bb81-60c01b32c1f0 · outbound

This paper cites Scientific Data 9(1), 122 (2022).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Scientific Data 9(1), 122 (2022)

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 7e347c4c-9dfc-4f77-a00b-67031b1b0737 · outbound

This paper cites UniMed-CLIP: Towards a Unified Image-Text Pretraining Paradigm for Diverse Medical Imaging Modalities.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift UniMed-CLIP: Towards a Unified Image-Text Pretraining Paradigm for Diverse Medical Imaging Modalities

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 4db2a01a-475d-4c77-afd8-24fdc0fd7782 · outbound

This paper cites Scientific Data 4(1), 170177 (2017) 10.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Scientific Data 4(1), 170177 (2017) 10

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 63cc40d0-b262-4340-817d-029cb79f95f7 · outbound

This paper cites European Radiology Experimental5(1), 40 (2021).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift European Radiology Experimental5(1), 40 (2021)

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 23b31f97-a073-453a-9c55-07bc9688e57d · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation e9076dfd-1fa0-4b07-b5d9-5e5f9acb9d86 · outbound

This paper cites Nature616, 259–265 (2023).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Nature616, 259–265 (2023)

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation eeb89741-38ba-4b97-8147-76027561f250 · outbound

This paper cites Academic Radiology19(2), 236–248 (2012).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Academic Radiology19(2), 236–248 (2012)

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 3dea6379-2f56-49e8-83b5-8b96db4a8ddc · outbound

This paper cites Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 511ad54d-d15b-4408-b374-b82f660a5402 · outbound

This paper cites Scientific Data10(1), 277 (2023).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Scientific Data10(1), 277 (2023)

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation f0420e6f-9c17-4147-bd80-28e35bc0f5b8 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift DINOv2: Learning Robust Visual Features without Supervision

Reference 27

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Observation 2218a3f0-0d0b-41f4-b8d4-758a34e50ef6 · outbound

This paper cites Biomedical Engineering Letters14(2), 317–330 (2024).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Biomedical Engineering Letters14(2), 317–330 (2024)

Reference 28

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Observation 606d42de-0379-4c71-b6a7-a5293001877d · outbound

This paper cites Radiology314(2), e240597 (2025).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Radiology314(2), e240597 (2025)

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-14T12:21:48.661331Z

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Observation 72f32b20-855d-400b-b6e3-2d141d6fb2c4 · outbound

This paper cites Nature Machine Intelligence7(1), 119–130 (2025).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Nature Machine Intelligence7(1), 119–130 (2025)

Reference 30

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Observation 0bce7578-8a9e-4bb9-a74c-1d1c7c4add05 · outbound

This paper cites an unresolved cited work.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Unresolved cited work

Reference 31

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Observation 9607c92f-9a3d-4434-99ad-66a5c5a723ce · outbound

This paper cites MedGemma Technical Report.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift MedGemma Technical Report

Reference 32

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Observation 633d476e-8f40-4eef-a456-e8c563525d67 · outbound

This paper cites DINOv3.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift DINOv3

Reference 33

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Observation c9e83000-55dc-4b27-8001-24b89505982c · outbound

This paper cites Apollo - University of Cambridge Repository (2015).

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift Apollo - University of Cambridge Repository (2015)

Reference 34

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Observation b64dd8ed-f64b-4468-a381-6199f7649830 · outbound

This paper cites BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs.

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

Reference 35

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Pith citing papers

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