Paper Citation Record · LEDGER

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis

As of 13 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2506.08849.

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

pith.paper-citation-record.v1
2506.08849 v4

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-19T10:34:28.875334Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:46:25.972641Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T15:46:28.009090Z

Reference resolution

38 of 38 outbound references displayed

verified exact11
verified fuzzy17
unresolved2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c62d2fdf-a016-4ce7-9d0b-43593e501e29 · outbound

This paper cites Cancer Imaging8(1), 48–56 (2008).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Cancer Imaging8(1), 48–56 (2008)

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:37:14.680763Z

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Observation 7af0f095-e35a-48c6-b3ce-65822e021d4a · outbound

This paper cites American Journal of Roentgenology184(5), 1691–1699 (2005).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis American Journal of Roentgenology184(5), 1691–1699 (2005)

Reference 2

Resolution: malformed identifier; doi_truncated, observed 2026-05-19T10:37:14.682623Z

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Observation 3e3b673b-1449-4e96-8b00-6b89b2ccf600 · outbound

This paper cites Data in Brief28, 104863 (2020).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Data in Brief28, 104863 (2020)

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:37:14.685496Z

Source-reported events for the cited work

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Observation c7616b45-e46c-4768-acc0-b81bd5906d5f · outbound

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

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis On the Opportunities and Risks of Foundation Models

Reference 4

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Observation 09bb5f10-a22c-423a-b4e6-974c65532fed · outbound

This paper cites American Journal of Roentgenology204(2), 234–240 (2015).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis American Journal of Roentgenology204(2), 234–240 (2015)

Reference 5

Resolution: verified exact; doi, observed 2026-05-19T10:37:14.699064Z

Source-reported events for the cited work

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Observation d5698c47-a5ba-4dd6-952b-c88bd3087f8c · outbound

This paper cites In: 2009 IEEE conference on computer vision and pattern recognition.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis In: 2009 IEEE conference on computer vision and pattern recognition

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.983603Z

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Observation a9146e76-2733-48dd-bd67-6f15f20aa00c · outbound

This paper cites In: North American Chapter of the Association for Computational Linguistics (2019).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis In: North American Chapter of the Association for Computational Linguistics (2019)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.981698Z

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Observation a18ae110-5f86-45ee-b14d-4347e8e05511 · outbound

This paper cites Does CLIP Benefit Visual Question Answering in the Medical Domain as Much as it Does in the General Domain?.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Does CLIP Benefit Visual Question Answering in the Medical Domain as Much as it Does in the General Domain?

Reference 8

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Observation d9ab895f-31ff-46d4-b37c-f0b113184e0b · outbound

This paper cites Com- puters in Biology and Medicine155, 106389 (2023).https://doi.org/https: //doi.org/10.1016/j.compbiomed.2022.106389,https://www.sciencedirect.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Com- puters in Biology and Medicine155, 106389 (2023).https://doi.org/https: //doi.org/10.1016/j.compbiomed.2022.106389,https://www.sciencedirect

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:37:14.697175Z

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Observation 41b17b31-81c8-4bc7-a1b1-cd7a79e0db82 · outbound

This paper cites Journal of Medical Imaging and Radiation Sciences 55(3), 101544 (2024).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Journal of Medical Imaging and Radiation Sciences 55(3), 101544 (2024)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.977880Z

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Observation afa906f7-ae4d-47fa-a08f-f26bdc97ea62 · outbound

This paper cites BMC cancer 25(1), 73 (2025).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis BMC cancer 25(1), 73 (2025)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.974191Z

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Observation 0ff769a3-90f1-47e8-b96f-f3479601864e · outbound

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

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.972626Z

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Observation 4f22f558-c58c-4d34-a889-6c14d3667d26 · outbound

This paper cites ICLR1(2), 3 (2022).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis ICLR1(2), 3 (2022)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.971001Z

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Observation 1b9ac178-2aff-49af-b7eb-4b438f639e43 · outbound

This paper cites an unresolved cited work.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Unresolved cited work

Reference 14

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Observation 4e3ce1c6-047f-4cb4-a4d4-8fd457d942d9 · outbound

This paper cites Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society112, 102326 (2023).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society112, 102326 (2023)

Reference 15

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Observation b72b4250-6cab-48ee-9990-689b85dd8c83 · outbound

This paper cites Medical Image Analysis96, 103202 (2024).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Medical Image Analysis96, 103202 (2024)

Reference 16

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Observation 8a921c72-e449-4b91-8553-7bc07dc0e151 · outbound

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

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis UniMed-CLIP: Towards a Unified Image-Text Pretraining Paradigm for Diverse Medical Imaging Modalities

Reference 17

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Observation 6253ca40-50d6-47a7-83e8-87a0d6b4681a · outbound

This paper cites Segment Anything.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Segment Anything

Reference 18

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Observation d352d193-fc8d-47dd-9854-cebf598eb3e7 · outbound

This paper cites IEEE Transactions on Medical Imaging (2024).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis IEEE Transactions on Medical Imaging (2024)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.990637Z

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Observation 71d09124-9754-4316-a281-8eef44a26cfc · outbound

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

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.987011Z

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Observation f71925d8-a409-4981-bd46-65da7163b280 · outbound

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

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis In: Proceedings of the IEEE/CVF international conference on computer vision

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.988693Z

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Observation 0cb2b23d-37bd-4950-a74d-13ddaaf658e5 · outbound

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

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis In: Pro- ceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.982676Z

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Observation 9968d281-7f0a-4ff1-a00d-981b08012559 · outbound

This paper cites arXiv:2411.16222 (2024).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis arXiv:2411.16222 (2024)

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:37:15.135093Z

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Observation 7664a232-90a5-4b13-a6f7-17530da8d901 · outbound

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

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis DINOv2: Learning Robust Visual Features without Supervision

Reference 24

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Observation fe07acec-4df6-441e-9826-0d1172f32cea · outbound

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Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Unresolved cited work

Reference 25

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Observation cc4c5990-60c5-4e4d-a127-a9c471a17217 · outbound

This paper cites In: International Conference on Medical Imaging with Deep Learning (2023).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis In: International Conference on Medical Imaging with Deep Learning (2023)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.979669Z

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Observation acad4964-4ead-4303-9103-e26f32d0f6a9 · outbound

This paper cites IEEE Access13, 97208–97227 (2025).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis IEEE Access13, 97208–97227 (2025)

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:37:14.692287Z

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Observation 330e53aa-a1c7-409f-9d16-bfbc97355a9f · outbound

This paper cites In: International conference on machine learning.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis In: International conference on machine learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.965694Z

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Observation 913d710c-976c-451a-93a4-8936404eaf9d · outbound

This paper cites an unresolved cited work.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Unresolved cited work

Reference 29

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Observation 15eea4df-a1d8-4ce9-83a0-a5b46fe51095 · outbound

This paper cites In: Medical image computing and computer-assisted interven- tion–MICCAI 2015: 18th international conference, Munich, Germany, October 5-9, 2015, proceedings, part III 18.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis In: Medical image computing and computer-assisted interven- tion–MICCAI 2015: 18th international conference, Munich, Germany, October 5-9, 2015, proceedings, part III 18

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:03.000417Z

Source-reported events for the cited work

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Observation 0e66945b-ba33-46d4-a470-d28a53676aa4 · outbound

This paper cites Journal of Clinical Ultrasound 23(3), 179–184 (1995).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Journal of Clinical Ultrasound 23(3), 179–184 (1995)

Reference 31

Resolution: verified exact; doi, observed 2026-05-19T10:37:14.689400Z

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Observation 4c37b552-6b47-4ad4-b7af-f6e3dc61430a · outbound

This paper cites Advances in neural information processing systems35, 5696–5710 (2022).

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Advances in neural information processing systems35, 5696–5710 (2022)

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.998733Z

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Observation d4615dde-b75d-499b-8d75-ed01fe00a98d · outbound

This paper cites Proceedings of the Conference on Empirical Methods in Natural Language Processing.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Proceedings of the Conference on Empirical Methods in Natural Language Processing

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T10:43:02.996859Z

Source-reported events for the cited work

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Observation c0f62806-ba9a-4209-b7e8-de830d02e733 · outbound

This paper cites Demystifying CLIP Data.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Demystifying CLIP Data

Reference 34

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Observation cc56687e-9f39-4fef-96c2-607564c937b2 · outbound

This paper cites Qwen3 Technical Report.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis Qwen3 Technical Report

Reference 35

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T10:37:15.126491Z

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Observation a74ac488-29a3-4207-8431-7f4cf383607d · outbound

This paper cites 5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis 5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:37:15.123356Z

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Observation 185e2479-273f-4584-acae-a28f3662107a · outbound

This paper cites part i: Normal lymph nodes.

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis part i: Normal lymph nodes

Reference 37

Resolution: verified exact; doi, observed 2026-05-19T10:37:14.687514Z

Source-reported events for the cited work

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Observation e2d1c597-8302-4dbd-825b-57ab89d3e072 · outbound

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

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

Reference 38

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T10:37:15.120210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

Observation f2c4eb3d-9daa-4e4f-80ba-10c1a067645a · inbound

BleedOrigin: Dynamic Bleeding Source Localization in Endoscopic Submucosal Dissection via Dual-Stage Detection and Tracking cites this paper.

BleedOrigin: Dynamic Bleeding Source Localization in Endoscopic Submucosal Dissection via Dual-Stage Detection and Tracking Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:46:28.018561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.