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Paper Citation Record · LEDGER

FedEFM: Federated Endovascular Foundation Model with Unseen Data

As of 15 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2501.16992.

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

pith.paper-citation-record.v1
2501.16992 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T05:19:04.307148Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

62 of 62 outbound references displayed

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  • verified fuzzy49
  • unresolved9
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2eed932d-4fc7-48b3-9a91-271deba2cc72 · outbound

This paper cites A survey of catheter tracking concepts and methodologies,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data A survey of catheter tracking concepts and methodologies,

Reference 1

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Observation c8c0408a-8b78-4d10-b340-f1d6b625b7ab · outbound

This paper cites Cathsim: an open- source simulator for endovascular intervention,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Cathsim: an open- source simulator for endovascular intervention,

Reference 2

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d41c818c-bc20-4f24-9074-a817c677c6b0 · outbound

This paper cites Use of ultrasound to confirm guidewire position in hemodialysis catheter implantation,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Use of ultrasound to confirm guidewire position in hemodialysis catheter implantation,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 230fccfe-c509-4b67-a814-f717828fe659 · outbound

This paper cites Detecting the sensing area of a laparoscopic probe in minimally invasive cancer surgery,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Detecting the sensing area of a laparoscopic probe in minimally invasive cancer surgery,

Reference 4

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 05064287-2bb7-4302-8d33-4f71325e6fab · outbound

This paper cites Foundation model for endoscopy video analysis via large-scale self-supervised pre-train,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Foundation model for endoscopy video analysis via large-scale self-supervised pre-train,

Reference 5

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 5a3be4ba-a4c9-47b9-bde4-184082e3b734 · outbound

This paper cites Text-guided foundation model adaptation for pathological image classification,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Text-guided foundation model adaptation for pathological image classification,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6b198792-5472-4900-96de-61ba91c0f26e · outbound

This paper cites Learning transferable visual models from natural language supervision,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Learning transferable visual models from natural language supervision,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c3fdb481-ecff-49c8-8a3d-2523e25cf3d9 · outbound

This paper cites Scaling up visual and vision-language representation learning with noisy text supervision,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Scaling up visual and vision-language representation learning with noisy text supervision,

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7c3414b9-9196-4152-87f3-161a5b15d860 · outbound

This paper cites Lvm-med: Learning large-scale self-supervised vision models for medical imaging via second-order graph matching,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Lvm-med: Learning large-scale self-supervised vision models for medical imaging via second-order graph matching,

Reference 9

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 80f61b22-f779-49f2-a8dc-4585d91a7602 · outbound

This paper cites Secure, privacy-preserving and federated machine learning in medical imaging,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Secure, privacy-preserving and federated machine learning in medical imaging,

Reference 10

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation afaf17a0-c98d-497e-ba0f-8fb94b02b710 · outbound

This paper cites Simultaneous depth estimation and surgical tool segmentation in laparoscopic images,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Simultaneous depth estimation and surgical tool segmentation in laparoscopic images,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 5d093d7b-e42c-4849-b918-c30cf9676fda · outbound

This paper cites Harmofl: Harmonizing local and global drifts in federated learning on heterogeneous medical images,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Harmofl: Harmonizing local and global drifts in federated learning on heterogeneous medical images,

Reference 12

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation fb441a16-5e20-46c3-9658-6f07ad6f1c51 · outbound

This paper cites Fedcontrast-gpa: Heterogeneous federated optimization via local contrastive learning and global process-aware aggregation,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Fedcontrast-gpa: Heterogeneous federated optimization via local contrastive learning and global process-aware aggregation,

Reference 13

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 05a186aa-dc02-4570-b60d-0850d34df08d · outbound

This paper cites CathAction: A Benchmark for Endovascular Intervention Understanding.

FedEFM: Federated Endovascular Foundation Model with Unseen Data CathAction: A Benchmark for Endovascular Intervention Understanding

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 4bb7da09-7c88-4451-9393-41d4107401fc · outbound

This paper cites Guide-wire tracking during endovascular interventions,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Guide-wire tracking during endovascular interventions,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 9b249b37-e19b-442f-b0fc-e60d118c95c2 · outbound

This paper cites A real-time multifunctional framework for guidewire morpho- logical and positional analysis in interventional x-ray fluoroscopy,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data A real-time multifunctional framework for guidewire morpho- logical and positional analysis in interventional x-ray fluoroscopy,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 200f2d6e-d708-4e12-9de5-5feffa1166f2 · outbound

This paper cites Catheter segmentation in x-ray fluoroscopy using synthetic data and transfer learning with light u-nets,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Catheter segmentation in x-ray fluoroscopy using synthetic data and transfer learning with light u-nets,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 3867064e-bc67-4d2b-9d5f-b3b7bdb96fbb · outbound

This paper cites Mri-guided congenital cardiac catheterization and interven- tion: The future?.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Mri-guided congenital cardiac catheterization and interven- tion: The future?

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c1ac86b5-8c09-45a8-9ecf-33853ac08ca9 · outbound

This paper cites Factors influencing fluoroscopy time in endovascular treatment of abdominal aneurysms: a retrospective study,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Factors influencing fluoroscopy time in endovascular treatment of abdominal aneurysms: a retrospective study,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:03.921954Z digest=sha256:46930c51ff077b3ca77f2fc3d5743e0ebd1797bc7f6e9cf1b77fbdaf5a86cb2f

Observation b8d189c9-8674-40b7-a385-490fabbfab8e · outbound

This paper cites Multiple device segmen- tation for fluoroscopic imaging using multi-task learning,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Multiple device segmen- tation for fluoroscopic imaging using multi-task learning,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:03.929453Z digest=sha256:ad8dbc0cacc62fe8b709828bae44effc3e9def92eb32e26b1e3c8f7ac6d9f931

Observation d292f36c-e5d4-40ae-abde-dfc1b9e6e266 · outbound

This paper cites Intraoperative stent segmentation in x-ray fluoroscopy for endovascular aortic repair,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Intraoperative stent segmentation in x-ray fluoroscopy for endovascular aortic repair,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:03.940320Z digest=sha256:5afcb7d9d48341bc5e4de31b656598f9b24420abfacbbe73ea948b85a870c207

Observation 3513758d-7431-4232-be45-bdf8cdf98f68 · outbound

This paper cites A tensor-based catheter and wire detection and tracking framework and its clinical applications,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data A tensor-based catheter and wire detection and tracking framework and its clinical applications,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:03.947392Z digest=sha256:1b4d21b24557e592ae2ca0fae57f9965bba28a0a7e30c5a712c7658df5c5f7db

Observation a4af518c-5021-465a-844d-4ebd4753c06a · outbound

This paper cites AiAReSeg: Catheter Detection and Segmentation in Interventional Ultrasound using Transformers.

FedEFM: Federated Endovascular Foundation Model with Unseen Data AiAReSeg: Catheter Detection and Segmentation in Interventional Ultrasound using Transformers

Reference 23

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local_arxiv, observed 2026-08-10T05:19:04.636955Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation f238623b-5f77-4804-bd2b-0383f9d4838f · outbound

This paper cites Real time detection and tracking of guide wire/catheter for interventional embolization robot based on deep learning,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Real time detection and tracking of guide wire/catheter for interventional embolization robot based on deep learning,

Reference 24

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raw_fallback, observed 2026-08-10T05:19:05.659074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 939b9000-e443-4d56-9bce-ebdf2c8081b6 · outbound

This paper cites Guidewire endpoint detection based on pixel-adjacent relation during robot-assisted intravascular catheterization: In vivo mammalian models,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Guidewire endpoint detection based on pixel-adjacent relation during robot-assisted intravascular catheterization: In vivo mammalian models,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:03.988870Z digest=sha256:8dfb313f7fc2fae76d033003e9dc02b3e8ca1ccec414e3f2c8f9ee7be7185b0a

Observation a07a7f82-a491-4d26-9c98-6ea764708403 · outbound

This paper cites End-to-end real-time catheter segmentation with optical flow-guided warping during en- dovascular intervention,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data End-to-end real-time catheter segmentation with optical flow-guided warping during en- dovascular intervention,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d112de40-2b59-483d-96cc-89c28bbeda9f · outbound

This paper cites MedCLIP: Contrastive Learning from Unpaired Medical Images and Text.

FedEFM: Federated Endovascular Foundation Model with Unseen Data MedCLIP: Contrastive Learning from Unpaired Medical Images and Text

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation dec2809f-b25a-4f35-8e4b-6bf40a64e5d7 · outbound

This paper cites Segment anything in medical images,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Segment anything in medical images,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.007531Z digest=sha256:e1af2ffa41b93edffb87232ae0cb8daa182739ac01a12659460fe03ede84a602

Observation 081ad7ad-be63-41c3-8030-f58be42bfdc0 · outbound

This paper cites MedCLIP-SAM: Bridging Text and Image Towards Universal Medical Image Segmentation.

FedEFM: Federated Endovascular Foundation Model with Unseen Data MedCLIP-SAM: Bridging Text and Image Towards Universal Medical Image Segmentation

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T05:19:04.018790Z digest=sha256:788c7a21eaa7139643eb9cdda1c5be374ffe55df82be6eaaa9fde5d0fa1141be

Observation cb6c071b-a55b-48c2-8339-afe68c21344f · outbound

This paper cites Federated Learning: Opportunities and Challenges.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Federated Learning: Opportunities and Challenges

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T05:19:04.025594Z digest=sha256:61ef14422250e8fe82f0764631af9c331d3386f08ab9fa76b6af10bbdcdbc107

Observation 34822aff-53ad-46c2-bf6d-797531ebb248 · outbound

This paper cites Client-level differential privacy via adaptive intermediary in federated medical imaging,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Client-level differential privacy via adaptive intermediary in federated medical imaging,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation f9bff328-6e6a-462a-847e-4cd536e06ec6 · outbound

This paper cites Feddat: An approach for foundation model finetuning in multi-modal heteroge- neous federated learning,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Feddat: An approach for foundation model finetuning in multi-modal heteroge- neous federated learning,

Reference 32

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raw_fallback, observed 2026-08-10T05:19:05.510336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.040000Z digest=sha256:9f853adbe7e2c9b2dee1447e443253d2dbccab1d6fc736177ebedfd5919f31d0

Observation f93abec5-263d-4bbf-8ca3-017674cd62fd · outbound

This paper cites FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation.

FedEFM: Federated Endovascular Foundation Model with Unseen Data FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation

Reference 33

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verified exact
local_arxiv, observed 2026-08-10T05:19:04.498560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.046731Z digest=sha256:6632fa988d3d874d5e8216f2ca8b07c3fec184d88f8884a81f192a1ebd1ad890

Observation 91a30d56-5e50-4fde-a7f1-51e65ad32f07 · outbound

This paper cites Differ- entially private federated learning with an adaptive noise mechanism,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Differ- entially private federated learning with an adaptive noise mechanism,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.470580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.060528Z digest=sha256:73104849b905c745f8ecc29a9105cc5fa5afef7e890f910e93c9e9ae0e2764c1

Observation b1a44d8d-57cf-46fa-9837-1f1c6ca658e0 · outbound

This paper cites Differentially private federated multi-task learning framework for enhancing human- to-virtual connectivity in human digital twin,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Differentially private federated multi-task learning framework for enhancing human- to-virtual connectivity in human digital twin,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.438133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.066093Z digest=sha256:59d3edc0cbd636f2ef60abef3de5cc002e13d5eba65c8a62d5cafa6da58489dd

Observation a2c260e1-a736-4d00-b6ff-f678a5a177ba · outbound

This paper cites Heteroge- neous differential-private federated learning: Trading privacy for utility truthfully,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Heteroge- neous differential-private federated learning: Trading privacy for utility truthfully,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.408338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.075912Z digest=sha256:f88d37151303deb604033d53394b0a1389f2e5ad0c442e50aed2dcce7f9afc8e

Observation 9f18090a-a85f-4d3c-a390-0ef9313ed310 · outbound

This paper cites Towards personalized federated learning via heterogeneous model reassembly,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Towards personalized federated learning via heterogeneous model reassembly,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.383221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.080272Z digest=sha256:c1996ed8cf61d765498f8c14faa3303699cd90c76e52521b023afa5fcf803e8e

Observation fe8fd4ff-4ee3-4e4c-b270-711679477eaa · outbound

This paper cites Feddg: Fed- erated domain generalization on medical image segmentation via episodic learning in continuous frequency space,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Feddg: Fed- erated domain generalization on medical image segmentation via episodic learning in continuous frequency space,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.356364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.093708Z digest=sha256:232cd09b027bd806c0612164de7b01cadbec49022d62206d0ee483ca7ad40590

Observation 38148d30-c69d-42b3-87b6-106bd6aaeae9 · outbound

This paper cites FUNAvg: Federated Uncertainty Weighted Averaging for Datasets with Diverse Labels.

FedEFM: Federated Endovascular Foundation Model with Unseen Data FUNAvg: Federated Uncertainty Weighted Averaging for Datasets with Diverse Labels

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-10T05:19:04.449821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.102518Z digest=sha256:8fc6a244d95f0e355ceae7944ad8370ecaca62cc3ba2669c80893d052929c279

Observation 2def40b5-2062-4f40-9886-707fb1404fde · outbound

This paper cites Distilling the knowledge in a neural network,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Distilling the knowledge in a neural network,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.325011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.111623Z digest=sha256:57e956fc4d452a32a11b4dfaf79fd2cfedfeb3134dc74a1c51de67e39cb9b2b9

Observation d29ebc31-a870-4d8c-bf97-c1d63e386ac5 · outbound

This paper cites Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T05:19:04.120492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T05:19:04.120492Z digest=sha256:5f8bfc58cb4e3754d5e89eadf25003e7bb867c9406be143f611724fcc91bce3a

Observation 0125151b-eef8-4d92-82c1-348117bb1a2d · outbound

This paper cites Deepemd: Few-shot image classification with differentiable earth mover’s distance and structured classifiers,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Deepemd: Few-shot image classification with differentiable earth mover’s distance and structured classifiers,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.299911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.126909Z digest=sha256:5962f914616c2a7597f368531a80352be3ea1591e9f053490be05cfaa9e1d57e

Observation 3d8869f8-b4b5-4048-b1c4-e3254aa5a289 · outbound

This paper cites Differential earth mover’s distance with its applications to visual tracking,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Differential earth mover’s distance with its applications to visual tracking,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.276995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.135513Z digest=sha256:ea373e7a22bb879ed05ade0544df394c215a3fd700141333f6fdfc8df300cab6

Observation af3ccf72-6c99-4b14-99d1-4307af54191a · outbound

This paper cites Throughput-optimal topology design for cross-silo federated learning,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Throughput-optimal topology design for cross-silo federated learning,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.255707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.158029Z digest=sha256:876a1592da2cf1e4c7295321e52cd72ae0ac540887eed2a8428b53c2d94296b9

Observation 1eda26cf-b2d3-4821-ba00-4b0f5ca3d646 · outbound

This paper cites Addressing non-iid problem in federated autonomous driving with contrastive divergence loss,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Addressing non-iid problem in federated autonomous driving with contrastive divergence loss,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.223459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.166490Z digest=sha256:eea45ce8472502f44a10b223f8825d56d45135770c464c222af151ffb36dc9af

Observation 1ce62c67-7c42-4286-8dec-5c153341b46b · outbound

This paper cites Au- tonomous navigation in complex environments with deep multimodal fusion network,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Au- tonomous navigation in complex environments with deep multimodal fusion network,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.187205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.173421Z digest=sha256:5642bae50da5892e53e8e1642f536bf4f6c61a43d30da776918b4ad1d671233d

Observation 18aa1b18-242b-4897-939a-afa3db096df5 · outbound

This paper cites The ”wake-sleep.

FedEFM: Federated Endovascular Foundation Model with Unseen Data The ”wake-sleep

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.162955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.179836Z digest=sha256:3715c7006fbebcbb0949b61a3b3cd576db153be62311aefb0f1a230a19d3941b

Observation 5a994936-5d5a-4a69-b84a-a3de3915bea8 · outbound

This paper cites Comparing algorithms for automated vessel segmentation in computed tomogra- phy scans of the lung: the vessel12 study,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Comparing algorithms for automated vessel segmentation in computed tomogra- phy scans of the lung: the vessel12 study,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.132835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.185954Z digest=sha256:46b9ab05f84346ca74cd707fcb3ae5e36e46ecc0888ed342c79a45030b9851be

Observation e4f594e4-1c8c-4033-86d8-8a471e15c693 · outbound

This paper cites Ridge-based vessel segmentation in color images of the retina,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Ridge-based vessel segmentation in color images of the retina,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.102820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.191354Z digest=sha256:e95bcace5a035bf23c5bdaa4a28414a7155f055abae6a760829f590647f1e786

Observation 18b17e09-5bfe-46a2-b6c6-a3f098a81446 · outbound

This paper cites Imaging intact human organs with local resolution of cellular structures using hierarchical phase-contrast tomography,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Imaging intact human organs with local resolution of cellular structures using hierarchical phase-contrast tomography,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.075485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.201342Z digest=sha256:6c2372b911763c4cd9230568816e2103e95e3ccaa9454e0f500f27902443f805

Observation e6abcee7-ee69-4ede-9c5a-0c9640de912d · outbound

This paper cites The medical segmentation decathlon,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data The medical segmentation decathlon,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.041796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.209857Z digest=sha256:ec5d535e5d11912247f2ba99d07be293967e7bc929aa96ff708a92ee9d1ad04c

Observation 12a2af76-1a35-4c45-ade9-7d2fa0af0004 · outbound

This paper cites Radiographic assessment of cvc malpositioning: How can ai best support clinicians?.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Radiographic assessment of cvc malpositioning: How can ai best support clinicians?

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:05.006725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.217978Z digest=sha256:a0f185ddb808be12590c8ac6656c2be3be6585dd456187eba1bf4825dd560df7

Observation 5ce79c4d-e7d8-41a7-80d6-0f738747ca2c · outbound

This paper cites Shape-sensitive loss for catheter and guidewire segmentation,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Shape-sensitive loss for catheter and guidewire segmentation,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:04.974622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.226483Z digest=sha256:3dbc729db6c7d72f1df19d54273f413522b6812d512293d267cd34cf017f3b39

Observation aee1b24e-71c7-4972-8282-6475144cd1df · outbound

This paper cites Communication-efficient learning of deep networks from decentral- ized data,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Communication-efficient learning of deep networks from decentral- ized data,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:04.941341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.233262Z digest=sha256:d6afd227c8d3209f74889b1b7c7bfaccebc349fc9418aff75a6cd197dc39850e

Observation 76d12124-8c52-478c-997b-50d0984b95d6 · outbound

This paper cites Segment anything,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Segment anything,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:04.911132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.239437Z digest=sha256:c14c8c366ee5a0c6ea46b7864cbeb1b083ce6767e27acb4b5ef1d190529c88c3

Observation 68516651-1c07-4a7c-a1db-c7ccaba138e1 · outbound

This paper cites Model-contrastive federated learning,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Model-contrastive federated learning,

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-10T05:19:04.248946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T05:19:04.248946Z digest=sha256:135e1f71ff6e8553d01e46a2863f2e6340653d6e462340be25b779a0cd81899d

Observation 7e336d3a-89b7-46f8-9db1-b0ff3e013d5c · outbound

This paper cites On variants of shortest-path betweenness centrality and their generic computation,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data On variants of shortest-path betweenness centrality and their generic computation,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:04.871124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.255232Z digest=sha256:30729c2948bcbaaa259d30e41cedc9c6bf4e9568a334262a9075eed40636e06b

Observation 9ba126e8-185f-4310-a0a0-9b797bbb4d30 · outbound

This paper cites Matcha: Speeding up decentralized sgd via matching decomposition sampling,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Matcha: Speeding up decentralized sgd via matching decomposition sampling,

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-10T05:19:04.264449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T05:19:04.264449Z digest=sha256:09f2507a525bff9622d6f99a91bd10098918dcce68784074284268b34fd8f908

Observation c4b3efe5-8fbb-4fc1-801e-181cbe74e5a6 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-10T05:19:04.269755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T05:19:04.269755Z digest=sha256:cc02146d188794921452fdd7b8b510c7e49068ef2e4e22cb7d488874e407fa0a

Observation da616dc5-cd28-43b3-8214-12171bf7ae6e · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data U-net: Convolutional networks for biomedical image segmentation,

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-10T05:19:04.287533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T05:19:04.287533Z digest=sha256:00012278dcdcc63e32d4e2512413f28fe2f31b8d3a782ca65d943cb7532558a2

Observation cad18af4-d8e7-4319-a4f3-bfe509843db6 · outbound

This paper cites Transunet: Transformers make strong encoders for medical image segmentation,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Transunet: Transformers make strong encoders for medical image segmentation,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:04.768563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.294598Z digest=sha256:e436c57548eaecaef31cfa3ca81d119222a4abd35e09af33eec51fde29500001

Observation 815ab396-52a0-43e4-aa61-b15c93af3ab3 · outbound

This paper cites Swin-unet: Unet-like pure transformer for medical image segmentation,.

FedEFM: Federated Endovascular Foundation Model with Unseen Data Swin-unet: Unet-like pure transformer for medical image segmentation,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:19:04.742592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T05:19:04.307148Z digest=sha256:b41828dbae2fbda4b9464745ce42751ef918816cd6def3b8df5af75c9404f2fe

Pith citing papers

No inbound Pith citation observations are available.